Overview

Brought to you by YData

Dataset statistics

Number of variables153
Number of observations338094
Missing cells26940749
Missing cells (%)52.1%
Total size in memory394.7 MiB
Average record size in memory1.2 KiB

Variable types

Text153

Dataset

DescriptionNMNH Material Samples (USNM) 0049394-241126133413365
URLhttps://doi.org/10.15468/dl.ycwxgd

Alerts

license has constant value "CC0_1_0" Constant
publisher has constant value "National Museum of Natural History, Smithsonian Institution" Constant
institutionID has constant value "http://grbio.org/cool/142r-0w94" Constant
datasetName has constant value "NMNH Material Samples (USNM)" Constant
basisOfRecord has constant value "MATERIAL_SAMPLE" Constant
occurrenceStatus has constant value "PRESENT" Constant
organismName has constant value "EML" Constant
organismScope has constant value "2024-12-01T12:07:33.811Z" Constant
associatedOrganisms has constant value "2024-12-01T11:07:21.711Z" Constant
previousIdentifications has constant value "true" Constant
materialEntityRemarks has constant value "false" Constant
parentEventID has constant value "Panama" Constant
eventType has constant value "PAN.5_1" Constant
eventTime has constant value "Pinogana" Constant
identifiedByID has constant value "ACCEPTED" Constant
identificationVerificationStatus has constant value "26098c25-8f7f-4c71-97ac-1d3db181c65e" Constant
identificationRemarks has constant value "US" Constant
acceptedNameUsage has constant value "false" Constant
subtribe has constant value "EML" Constant
subgenus has constant value "true" Constant
protocol has constant value "EML" Constant
lastCrawled has constant value "2024-12-01T11:07:21.711Z" Constant
publishedByGbifRegion has constant value "NORTH_AMERICA" Constant
catalogNumber has 70677 (20.9%) missing values Missing
recordNumber has 181582 (53.7%) missing values Missing
recordedBy has 70120 (20.7%) missing values Missing
individualCount has 39347 (11.6%) missing values Missing
sex has 265741 (78.6%) missing values Missing
lifeStage has 209004 (61.8%) missing values Missing
preparations has 251111 (74.3%) missing values Missing
associatedSequences has 305424 (90.3%) missing values Missing
occurrenceRemarks has 193547 (57.2%) missing values Missing
organismName has 338093 (> 99.9%) missing values Missing
organismScope has 338093 (> 99.9%) missing values Missing
associatedOrganisms has 338093 (> 99.9%) missing values Missing
previousIdentifications has 338093 (> 99.9%) missing values Missing
materialEntityRemarks has 338093 (> 99.9%) missing values Missing
verbatimLabel has 338089 (> 99.9%) missing values Missing
materialSampleID has 84986 (25.1%) missing values Missing
eventID has 338092 (> 99.9%) missing values Missing
parentEventID has 338093 (> 99.9%) missing values Missing
eventType has 338093 (> 99.9%) missing values Missing
fieldNumber has 267153 (79.0%) missing values Missing
eventDate has 16903 (5.0%) missing values Missing
eventTime has 338093 (> 99.9%) missing values Missing
startDayOfYear has 19910 (5.9%) missing values Missing
endDayOfYear has 19910 (5.9%) missing values Missing
year has 17140 (5.1%) missing values Missing
month has 22792 (6.7%) missing values Missing
day has 52010 (15.4%) missing values Missing
verbatimEventDate has 235843 (69.8%) missing values Missing
habitat has 302025 (89.3%) missing values Missing
locationID has 284620 (84.2%) missing values Missing
higherGeography has 4531 (1.3%) missing values Missing
continent has 57738 (17.1%) missing values Missing
waterBody has 231346 (68.4%) missing values Missing
islandGroup has 315374 (93.3%) missing values Missing
island has 279260 (82.6%) missing values Missing
countryCode has 11127 (3.3%) missing values Missing
stateProvince has 66137 (19.6%) missing values Missing
county has 140475 (41.5%) missing values Missing
locality has 34045 (10.1%) missing values Missing
verbatimElevation has 322170 (95.3%) missing values Missing
verbatimDepth has 336615 (99.6%) missing values Missing
minimumDistanceAboveSurfaceInMeters has 338092 (> 99.9%) missing values Missing
decimalLatitude has 73462 (21.7%) missing values Missing
decimalLongitude has 73462 (21.7%) missing values Missing
coordinateUncertaintyInMeters has 327083 (96.7%) missing values Missing
pointRadiusSpatialFit has 338090 (> 99.9%) missing values Missing
verbatimCoordinateSystem has 329029 (97.3%) missing values Missing
georeferencedBy has 338090 (> 99.9%) missing values Missing
georeferenceProtocol has 255273 (75.5%) missing values Missing
georeferenceRemarks has 328595 (97.2%) missing values Missing
latestEonOrHighestEonothem has 338090 (> 99.9%) missing values Missing
earliestEraOrLowestErathem has 338090 (> 99.9%) missing values Missing
latestEraOrHighestErathem has 338090 (> 99.9%) missing values Missing
earliestPeriodOrLowestSystem has 338091 (> 99.9%) missing values Missing
latestPeriodOrHighestSystem has 338091 (> 99.9%) missing values Missing
latestEpochOrHighestSeries has 338090 (> 99.9%) missing values Missing
highestBiostratigraphicZone has 338090 (> 99.9%) missing values Missing
lithostratigraphicTerms has 338090 (> 99.9%) missing values Missing
member has 338091 (> 99.9%) missing values Missing
verbatimIdentification has 338090 (> 99.9%) missing values Missing
identificationQualifier has 333028 (98.5%) missing values Missing
typeStatus has 331537 (98.1%) missing values Missing
identifiedBy has 226045 (66.9%) missing values Missing
identifiedByID has 338090 (> 99.9%) missing values Missing
identificationVerificationStatus has 338090 (> 99.9%) missing values Missing
identificationRemarks has 338090 (> 99.9%) missing values Missing
taxonID has 338090 (> 99.9%) missing values Missing
scientificNameID has 338092 (> 99.9%) missing values Missing
acceptedNameUsageID has 6111 (1.8%) missing values Missing
namePublishedInID has 338090 (> 99.9%) missing values Missing
acceptedNameUsage has 338090 (> 99.9%) missing values Missing
parentNameUsage has 338090 (> 99.9%) missing values Missing
originalNameUsage has 338090 (> 99.9%) missing values Missing
nameAccordingTo has 338090 (> 99.9%) missing values Missing
namePublishedIn has 338090 (> 99.9%) missing values Missing
namePublishedInYear has 338091 (> 99.9%) missing values Missing
higherClassification has 5891 (1.7%) missing values Missing
phylum has 6808 (2.0%) missing values Missing
class has 52277 (15.5%) missing values Missing
order has 30344 (9.0%) missing values Missing
superfamily has 338091 (> 99.9%) missing values Missing
family has 19906 (5.9%) missing values Missing
subfamily has 338090 (> 99.9%) missing values Missing
subtribe has 338090 (> 99.9%) missing values Missing
genus has 34392 (10.2%) missing values Missing
genericName has 34393 (10.2%) missing values Missing
subgenus has 338090 (> 99.9%) missing values Missing
specificEpithet has 89523 (26.5%) missing values Missing
infraspecificEpithet has 328999 (97.3%) missing values Missing
cultivarEpithet has 338090 (> 99.9%) missing values Missing
verbatimTaxonRank has 338090 (> 99.9%) missing values Missing
vernacularName has 338090 (> 99.9%) missing values Missing
nomenclaturalCode has 338090 (> 99.9%) missing values Missing
taxonomicStatus has 6108 (1.8%) missing values Missing
nomenclaturalStatus has 338091 (> 99.9%) missing values Missing
taxonRemarks has 338091 (> 99.9%) missing values Missing
elevation has 248950 (73.6%) missing values Missing
elevationAccuracy has 284393 (84.1%) missing values Missing
depth has 262666 (77.7%) missing values Missing
depthAccuracy has 272182 (80.5%) missing values Missing
distanceFromCentroidInMeters has 335404 (99.2%) missing values Missing
issue has 45626 (13.5%) missing values Missing
mediaType has 324090 (95.9%) missing values Missing
acceptedTaxonKey has 6112 (1.8%) missing values Missing
phylumKey has 6812 (2.0%) missing values Missing
classKey has 52277 (15.5%) missing values Missing
orderKey has 30347 (9.0%) missing values Missing
familyKey has 19910 (5.9%) missing values Missing
genusKey has 34396 (10.2%) missing values Missing
speciesKey has 89520 (26.5%) missing values Missing
species has 89520 (26.5%) missing values Missing
acceptedScientificName has 6112 (1.8%) missing values Missing
verbatimScientificName has 24039 (7.1%) missing values Missing
typifiedName has 338060 (> 99.9%) missing values Missing
repatriated has 10837 (3.2%) missing values Missing
gbifRegion has 12220 (3.6%) missing values Missing
level0Gid has 157741 (46.7%) missing values Missing
level0Name has 157741 (46.7%) missing values Missing
level1Gid has 158980 (47.0%) missing values Missing
level1Name has 158980 (47.0%) missing values Missing
level2Gid has 167237 (49.5%) missing values Missing
level2Name has 167249 (49.5%) missing values Missing
level3Gid has 300258 (88.8%) missing values Missing
level3Name has 300562 (88.9%) missing values Missing
iucnRedListCategory has 63456 (18.8%) missing values Missing
gbifID has unique values Unique
occurrenceID has unique values Unique

Reproduction

Analysis started2025-01-08 22:42:19.861325
Analysis finished2025-01-08 22:42:37.312514
Duration17.45 seconds
Software versionydata-profiling vv4.12.1
Download configurationconfig.json

Variables

gbifID
Text

Unique 

Distinct338094
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
2025-01-08T17:42:37.638320image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters3380940
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique338094 ?
Unique (%)100.0%

Sample

1st row4501677301
2nd row3027962301
3rd row3028050301
4th row3027962302
5th row3028050302
ValueCountFrequency (%)
4501677301 1
 
< 0.1%
4909491303 1
 
< 0.1%
3357130301 1
 
< 0.1%
3027962303 1
 
< 0.1%
3758404301 1
 
< 0.1%
3027962304 1
 
< 0.1%
3336913301 1
 
< 0.1%
3028050303 1
 
< 0.1%
4909491307 1
 
< 0.1%
3028050304 1
 
< 0.1%
Other values (338084) 338084
> 99.9%
2025-01-08T17:42:38.024043image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 540984
16.0%
3 466213
13.8%
9 357116
10.6%
2 356645
10.5%
8 331017
9.8%
4 317355
9.4%
1 298199
8.8%
5 263435
7.8%
7 254191
7.5%
6 195785
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3380940
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 540984
16.0%
3 466213
13.8%
9 357116
10.6%
2 356645
10.5%
8 331017
9.8%
4 317355
9.4%
1 298199
8.8%
5 263435
7.8%
7 254191
7.5%
6 195785
 
5.8%

Most occurring scripts

ValueCountFrequency (%)
Common 3380940
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 540984
16.0%
3 466213
13.8%
9 357116
10.6%
2 356645
10.5%
8 331017
9.8%
4 317355
9.4%
1 298199
8.8%
5 263435
7.8%
7 254191
7.5%
6 195785
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3380940
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 540984
16.0%
3 466213
13.8%
9 357116
10.6%
2 356645
10.5%
8 331017
9.8%
4 317355
9.4%
1 298199
8.8%
5 263435
7.8%
7 254191
7.5%
6 195785
 
5.8%

license
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
2025-01-08T17:42:38.077043image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters2366658
Distinct characters4
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCC0_1_0
2nd rowCC0_1_0
3rd rowCC0_1_0
4th rowCC0_1_0
5th rowCC0_1_0
ValueCountFrequency (%)
cc0_1_0 338094
100.0%
2025-01-08T17:42:38.166772image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 676188
28.6%
0 676188
28.6%
_ 676188
28.6%
1 338094
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1014282
42.9%
Uppercase Letter 676188
28.6%
Connector Punctuation 676188
28.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 676188
66.7%
1 338094
33.3%
Uppercase Letter
ValueCountFrequency (%)
C 676188
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 676188
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1690470
71.4%
Latin 676188
 
28.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 676188
40.0%
_ 676188
40.0%
1 338094
20.0%
Latin
ValueCountFrequency (%)
C 676188
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2366658
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
C 676188
28.6%
0 676188
28.6%
_ 676188
28.6%
1 338094
14.3%
Distinct10795
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
2025-01-08T17:42:38.271847image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters6761880
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2110 ?
Unique (%)0.6%

Sample

1st row2024-06-26T12:37:00Z
2nd row2021-10-14T09:12:00Z
3rd row2022-07-20T16:25:00Z
4th row2021-10-13T15:49:00Z
5th row2019-06-25T16:21:00Z
ValueCountFrequency (%)
2023-06-13t09:52:00z 2840
 
0.8%
2024-10-17t11:06:00z 2662
 
0.8%
2021-10-13t15:50:00z 2652
 
0.8%
2021-10-13t15:49:00z 2517
 
0.7%
2022-10-17t16:14:00z 2414
 
0.7%
2022-10-17t16:13:00z 2368
 
0.7%
2021-10-14t09:09:00z 2340
 
0.7%
2021-10-14t09:10:00z 2235
 
0.7%
2021-10-14t09:08:00z 2151
 
0.6%
2021-10-13t15:48:00z 2042
 
0.6%
Other values (10785) 313873
92.8%
2025-01-08T17:42:38.439070image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1616584
23.9%
2 1048026
15.5%
1 802624
11.9%
- 676188
10.0%
: 676188
10.0%
T 338094
 
5.0%
Z 338094
 
5.0%
3 230104
 
3.4%
4 213568
 
3.2%
5 202272
 
3.0%
Other values (4) 620138
 
9.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4733316
70.0%
Dash Punctuation 676188
 
10.0%
Other Punctuation 676188
 
10.0%
Uppercase Letter 676188
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1616584
34.2%
2 1048026
22.1%
1 802624
17.0%
3 230104
 
4.9%
4 213568
 
4.5%
5 202272
 
4.3%
7 196522
 
4.2%
6 170692
 
3.6%
9 151865
 
3.2%
8 101059
 
2.1%
Uppercase Letter
ValueCountFrequency (%)
T 338094
50.0%
Z 338094
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 676188
100.0%
Other Punctuation
ValueCountFrequency (%)
: 676188
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6085692
90.0%
Latin 676188
 
10.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1616584
26.6%
2 1048026
17.2%
1 802624
13.2%
- 676188
11.1%
: 676188
11.1%
3 230104
 
3.8%
4 213568
 
3.5%
5 202272
 
3.3%
7 196522
 
3.2%
6 170692
 
2.8%
Other values (2) 252924
 
4.2%
Latin
ValueCountFrequency (%)
T 338094
50.0%
Z 338094
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6761880
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1616584
23.9%
2 1048026
15.5%
1 802624
11.9%
- 676188
10.0%
: 676188
10.0%
T 338094
 
5.0%
Z 338094
 
5.0%
3 230104
 
3.4%
4 213568
 
3.2%
5 202272
 
3.0%
Other values (4) 620138
 
9.2%

publisher
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
2025-01-08T17:42:38.520525image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length59
Median length59
Mean length59
Min length59

Characters and Unicode

Total characters19947546
Distinct characters21
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNational Museum of Natural History, Smithsonian Institution
2nd rowNational Museum of Natural History, Smithsonian Institution
3rd rowNational Museum of Natural History, Smithsonian Institution
4th rowNational Museum of Natural History, Smithsonian Institution
5th rowNational Museum of Natural History, Smithsonian Institution
ValueCountFrequency (%)
national 338094
14.3%
museum 338094
14.3%
of 338094
14.3%
natural 338094
14.3%
history 338094
14.3%
smithsonian 338094
14.3%
institution 338094
14.3%
2025-01-08T17:42:38.631447image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 2366658
11.9%
i 2028564
10.2%
2028564
10.2%
a 1690470
 
8.5%
o 1690470
 
8.5%
n 1690470
 
8.5%
s 1352376
 
6.8%
u 1352376
 
6.8%
r 676188
 
3.4%
m 676188
 
3.4%
Other values (11) 4395222
22.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 15552324
78.0%
Space Separator 2028564
 
10.2%
Uppercase Letter 2028564
 
10.2%
Other Punctuation 338094
 
1.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 2366658
15.2%
i 2028564
13.0%
a 1690470
10.9%
o 1690470
10.9%
n 1690470
10.9%
s 1352376
8.7%
u 1352376
8.7%
r 676188
 
4.3%
m 676188
 
4.3%
l 676188
 
4.3%
Other values (4) 1352376
8.7%
Uppercase Letter
ValueCountFrequency (%)
N 676188
33.3%
M 338094
16.7%
H 338094
16.7%
S 338094
16.7%
I 338094
16.7%
Space Separator
ValueCountFrequency (%)
2028564
100.0%
Other Punctuation
ValueCountFrequency (%)
, 338094
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 17580888
88.1%
Common 2366658
 
11.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 2366658
13.5%
i 2028564
11.5%
a 1690470
9.6%
o 1690470
9.6%
n 1690470
9.6%
s 1352376
 
7.7%
u 1352376
 
7.7%
r 676188
 
3.8%
m 676188
 
3.8%
N 676188
 
3.8%
Other values (9) 3380940
19.2%
Common
ValueCountFrequency (%)
2028564
85.7%
, 338094
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19947546
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 2366658
11.9%
i 2028564
10.2%
2028564
10.2%
a 1690470
 
8.5%
o 1690470
 
8.5%
n 1690470
 
8.5%
s 1352376
 
6.8%
u 1352376
 
6.8%
r 676188
 
3.4%
m 676188
 
3.4%
Other values (11) 4395222
22.0%

institutionID
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
2025-01-08T17:42:38.686824image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length31
Median length31
Mean length31
Min length31

Characters and Unicode

Total characters10480914
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowhttp://grbio.org/cool/142r-0w94
2nd rowhttp://grbio.org/cool/142r-0w94
3rd rowhttp://grbio.org/cool/142r-0w94
4th rowhttp://grbio.org/cool/142r-0w94
5th rowhttp://grbio.org/cool/142r-0w94
ValueCountFrequency (%)
http://grbio.org/cool/142r-0w94 338094
100.0%
2025-01-08T17:42:38.788367image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 1352376
 
12.9%
o 1352376
 
12.9%
r 1014282
 
9.7%
g 676188
 
6.5%
t 676188
 
6.5%
4 676188
 
6.5%
h 338094
 
3.2%
1 338094
 
3.2%
w 338094
 
3.2%
0 338094
 
3.2%
Other values (10) 3380940
32.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6085692
58.1%
Other Punctuation 2028564
 
19.4%
Decimal Number 2028564
 
19.4%
Dash Punctuation 338094
 
3.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1352376
22.2%
r 1014282
16.7%
g 676188
11.1%
t 676188
11.1%
h 338094
 
5.6%
w 338094
 
5.6%
l 338094
 
5.6%
c 338094
 
5.6%
i 338094
 
5.6%
b 338094
 
5.6%
Decimal Number
ValueCountFrequency (%)
4 676188
33.3%
1 338094
16.7%
0 338094
16.7%
2 338094
16.7%
9 338094
16.7%
Other Punctuation
ValueCountFrequency (%)
/ 1352376
66.7%
. 338094
 
16.7%
: 338094
 
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 338094
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6085692
58.1%
Common 4395222
41.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1352376
22.2%
r 1014282
16.7%
g 676188
11.1%
t 676188
11.1%
h 338094
 
5.6%
w 338094
 
5.6%
l 338094
 
5.6%
c 338094
 
5.6%
i 338094
 
5.6%
b 338094
 
5.6%
Common
ValueCountFrequency (%)
/ 1352376
30.8%
4 676188
15.4%
1 338094
 
7.7%
0 338094
 
7.7%
- 338094
 
7.7%
2 338094
 
7.7%
. 338094
 
7.7%
: 338094
 
7.7%
9 338094
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10480914
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 1352376
 
12.9%
o 1352376
 
12.9%
r 1014282
 
9.7%
g 676188
 
6.5%
t 676188
 
6.5%
4 676188
 
6.5%
h 338094
 
3.2%
1 338094
 
3.2%
w 338094
 
3.2%
0 338094
 
3.2%
Other values (10) 3380940
32.3%
Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
2025-01-08T17:42:38.849596image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length45
Median length45
Mean length45
Min length45

Characters and Unicode

Total characters15214230
Distinct characters22
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowurn:uuid:18e3cd08-a962-4f0a-b72c-9a0b3600c5ad
2nd rowurn:uuid:f14c21a9-8cbf-4c8b-817f-d19d427e2dd6
3rd rowurn:uuid:f14c21a9-8cbf-4c8b-817f-d19d427e2dd6
4th rowurn:uuid:f14c21a9-8cbf-4c8b-817f-d19d427e2dd6
5th rowurn:uuid:60e28f81-e634-4869-aa3e-732caed713c8
ValueCountFrequency (%)
urn:uuid:18e3cd08-a962-4f0a-b72c-9a0b3600c5ad 119032
35.2%
urn:uuid:f14c21a9-8cbf-4c8b-817f-d19d427e2dd6 74362
22.0%
urn:uuid:60e28f81-e634-4869-aa3e-732caed713c8 42251
 
12.5%
urn:uuid:09c9cf5f-f5d3-48cc-b5c8-cd9b9fbd631f 41564
 
12.3%
urn:uuid:cc104cbf-fd8e-4801-9b71-36731a7db1a0 28248
 
8.4%
urn:uuid:59e56a59-8615-4e0c-841d-eb88f3876b22 24486
 
7.2%
urn:uuid:73d83e23-1999-42cd-b38a-c06a7d32d893 8151
 
2.4%
2025-01-08T17:42:38.958925image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1352376
 
8.9%
d 1154135
 
7.6%
c 1039600
 
6.8%
u 1014282
 
6.7%
8 916661
 
6.0%
0 796356
 
5.2%
a 774527
 
5.1%
1 740909
 
4.9%
9 705119
 
4.6%
: 676188
 
4.4%
Other values (12) 6044077
39.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6795599
44.7%
Decimal Number 6390067
42.0%
Dash Punctuation 1352376
 
8.9%
Other Punctuation 676188
 
4.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
d 1154135
17.0%
c 1039600
15.3%
u 1014282
14.9%
a 774527
11.4%
f 673171
9.9%
b 653347
9.6%
e 472255
6.9%
i 338094
 
5.0%
r 338094
 
5.0%
n 338094
 
5.0%
Decimal Number
ValueCountFrequency (%)
8 916661
14.3%
0 796356
12.5%
1 740909
11.6%
9 705119
11.0%
3 620084
9.7%
2 619077
9.7%
6 590600
9.2%
4 581803
9.1%
7 477790
7.5%
5 341668
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 1352376
100.0%
Other Punctuation
ValueCountFrequency (%)
: 676188
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8418631
55.3%
Latin 6795599
44.7%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1352376
16.1%
8 916661
10.9%
0 796356
9.5%
1 740909
8.8%
9 705119
8.4%
: 676188
8.0%
3 620084
7.4%
2 619077
7.4%
6 590600
7.0%
4 581803
6.9%
Other values (2) 819458
9.7%
Latin
ValueCountFrequency (%)
d 1154135
17.0%
c 1039600
15.3%
u 1014282
14.9%
a 774527
11.4%
f 673171
9.9%
b 653347
9.6%
e 472255
6.9%
i 338094
 
5.0%
r 338094
 
5.0%
n 338094
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15214230
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1352376
 
8.9%
d 1154135
 
7.6%
c 1039600
 
6.8%
u 1014282
 
6.7%
8 916661
 
6.0%
0 796356
 
5.2%
a 774527
 
5.1%
1 740909
 
4.9%
9 705119
 
4.6%
: 676188
 
4.4%
Other values (12) 6044077
39.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
2025-01-08T17:42:38.999924image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.750063592
Min length2

Characters and Unicode

Total characters1267874
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUSNM
2nd rowUSNM
3rd rowUSNM
4th rowUSNM
5th rowUS
ValueCountFrequency (%)
usnm 295843
87.5%
us 42251
 
12.5%
2025-01-08T17:42:39.097331image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 338094
26.7%
S 338094
26.7%
N 295843
23.3%
M 295843
23.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1267874
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U 338094
26.7%
S 338094
26.7%
N 295843
23.3%
M 295843
23.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 1267874
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U 338094
26.7%
S 338094
26.7%
N 295843
23.3%
M 295843
23.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1267874
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U 338094
26.7%
S 338094
26.7%
N 295843
23.3%
M 295843
23.3%
Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
2025-01-08T17:42:39.142575image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.982215005
Min length2

Characters and Unicode

Total characters1008269
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowENT
2nd rowIZ
3rd rowIZ
4th rowIZ
5th rowUS
ValueCountFrequency (%)
ent 119032
35.2%
iz 74362
22.0%
us 42251
 
12.5%
fish 41564
 
12.3%
herp 28248
 
8.4%
mamm 24486
 
7.2%
birds 8151
 
2.4%
2025-01-08T17:42:39.242164image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 147280
14.6%
I 124077
12.3%
N 119032
11.8%
T 119032
11.8%
S 91966
9.1%
Z 74362
7.4%
M 73458
7.3%
H 69812
6.9%
U 42251
 
4.2%
F 41564
 
4.1%
Other values (5) 105435
10.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1008269
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 147280
14.6%
I 124077
12.3%
N 119032
11.8%
T 119032
11.8%
S 91966
9.1%
Z 74362
7.4%
M 73458
7.3%
H 69812
6.9%
U 42251
 
4.2%
F 41564
 
4.1%
Other values (5) 105435
10.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 1008269
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 147280
14.6%
I 124077
12.3%
N 119032
11.8%
T 119032
11.8%
S 91966
9.1%
Z 74362
7.4%
M 73458
7.3%
H 69812
6.9%
U 42251
 
4.2%
F 41564
 
4.1%
Other values (5) 105435
10.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1008269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 147280
14.6%
I 124077
12.3%
N 119032
11.8%
T 119032
11.8%
S 91966
9.1%
Z 74362
7.4%
M 73458
7.3%
H 69812
6.9%
U 42251
 
4.2%
F 41564
 
4.1%
Other values (5) 105435
10.5%

datasetName
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
2025-01-08T17:42:39.284164image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length28
Median length28
Mean length28
Min length28

Characters and Unicode

Total characters9466632
Distinct characters17
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNMNH Material Samples (USNM)
2nd rowNMNH Material Samples (USNM)
3rd rowNMNH Material Samples (USNM)
4th rowNMNH Material Samples (USNM)
5th rowNMNH Material Samples (USNM)
ValueCountFrequency (%)
nmnh 338094
25.0%
material 338094
25.0%
samples 338094
25.0%
usnm 338094
25.0%
2025-01-08T17:42:39.377649image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1014282
10.7%
1014282
10.7%
a 1014282
10.7%
M 1014282
10.7%
e 676188
 
7.1%
l 676188
 
7.1%
S 676188
 
7.1%
p 338094
 
3.6%
U 338094
 
3.6%
( 338094
 
3.6%
Other values (7) 2366658
25.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4395222
46.4%
Uppercase Letter 3380940
35.7%
Space Separator 1014282
 
10.7%
Open Punctuation 338094
 
3.6%
Close Punctuation 338094
 
3.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 1014282
23.1%
e 676188
15.4%
l 676188
15.4%
p 338094
 
7.7%
s 338094
 
7.7%
i 338094
 
7.7%
m 338094
 
7.7%
r 338094
 
7.7%
t 338094
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
N 1014282
30.0%
M 1014282
30.0%
S 676188
20.0%
U 338094
 
10.0%
H 338094
 
10.0%
Space Separator
ValueCountFrequency (%)
1014282
100.0%
Open Punctuation
ValueCountFrequency (%)
( 338094
100.0%
Close Punctuation
ValueCountFrequency (%)
) 338094
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7776162
82.1%
Common 1690470
 
17.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1014282
13.0%
a 1014282
13.0%
M 1014282
13.0%
e 676188
8.7%
l 676188
8.7%
S 676188
8.7%
p 338094
 
4.3%
U 338094
 
4.3%
s 338094
 
4.3%
i 338094
 
4.3%
Other values (4) 1352376
17.4%
Common
ValueCountFrequency (%)
1014282
60.0%
( 338094
 
20.0%
) 338094
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9466632
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1014282
10.7%
1014282
10.7%
a 1014282
10.7%
M 1014282
10.7%
e 676188
 
7.1%
l 676188
 
7.1%
S 676188
 
7.1%
p 338094
 
3.6%
U 338094
 
3.6%
( 338094
 
3.6%
Other values (7) 2366658
25.0%

basisOfRecord
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
2025-01-08T17:42:39.424951image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length15
Median length15
Mean length15
Min length15

Characters and Unicode

Total characters5071410
Distinct characters10
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMATERIAL_SAMPLE
2nd rowMATERIAL_SAMPLE
3rd rowMATERIAL_SAMPLE
4th rowMATERIAL_SAMPLE
5th rowMATERIAL_SAMPLE
ValueCountFrequency (%)
material_sample 338094
100.0%
2025-01-08T17:42:39.551739image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 1014282
20.0%
M 676188
13.3%
E 676188
13.3%
L 676188
13.3%
T 338094
 
6.7%
R 338094
 
6.7%
I 338094
 
6.7%
_ 338094
 
6.7%
S 338094
 
6.7%
P 338094
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 4733316
93.3%
Connector Punctuation 338094
 
6.7%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 1014282
21.4%
M 676188
14.3%
E 676188
14.3%
L 676188
14.3%
T 338094
 
7.1%
R 338094
 
7.1%
I 338094
 
7.1%
S 338094
 
7.1%
P 338094
 
7.1%
Connector Punctuation
ValueCountFrequency (%)
_ 338094
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4733316
93.3%
Common 338094
 
6.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 1014282
21.4%
M 676188
14.3%
E 676188
14.3%
L 676188
14.3%
T 338094
 
7.1%
R 338094
 
7.1%
I 338094
 
7.1%
S 338094
 
7.1%
P 338094
 
7.1%
Common
ValueCountFrequency (%)
_ 338094
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5071410
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 1014282
20.0%
M 676188
13.3%
E 676188
13.3%
L 676188
13.3%
T 338094
 
6.7%
R 338094
 
6.7%
I 338094
 
6.7%
_ 338094
 
6.7%
S 338094
 
6.7%
P 338094
 
6.7%

occurrenceID
Text

Unique 

Distinct338094
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
2025-01-08T17:42:39.765163image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length63
Median length63
Mean length63
Min length63

Characters and Unicode

Total characters21299922
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique338094 ?
Unique (%)100.0%

Sample

1st rowhttp://n2t.net/ark:/65665/300028c5f-ea1d-4c01-9253-09524fc57db6
2nd rowhttp://n2t.net/ark:/65665/30006cd83-36b3-4629-86db-f5a28307189f
3rd rowhttp://n2t.net/ark:/65665/30007a443-7a0a-49a9-9c54-cae1342160a6
4th rowhttp://n2t.net/ark:/65665/300098b69-426b-451c-a675-27a1b7bb5b60
5th rowhttp://n2t.net/ark:/65665/3000a9424-501b-43e7-a337-ee632a8fa9d0
ValueCountFrequency (%)
http://n2t.net/ark:/65665/300028c5f-ea1d-4c01-9253-09524fc57db6 1
 
< 0.1%
http://n2t.net/ark:/65665/3000ef5c5-8164-4ad4-b093-79821f58ace8 1
 
< 0.1%
http://n2t.net/ark:/65665/300114e18-4d31-4558-acc1-47ce8dd8940c 1
 
< 0.1%
http://n2t.net/ark:/65665/300119514-9afd-4342-83ae-3526ac40f20f 1
 
< 0.1%
http://n2t.net/ark:/65665/300154f73-1f7a-4d73-8c43-7c6d66c03b0f 1
 
< 0.1%
http://n2t.net/ark:/65665/30015c5b5-263e-4d28-916f-89728207dfda 1
 
< 0.1%
http://n2t.net/ark:/65665/3001878d3-3d26-4b66-9ad5-77d6938de137 1
 
< 0.1%
http://n2t.net/ark:/65665/300187c30-1f5e-4401-a208-4e42206dc341 1
 
< 0.1%
http://n2t.net/ark:/65665/300193d42-6a2a-41b9-b203-29e571953cd6 1
 
< 0.1%
http://n2t.net/ark:/65665/3001b5554-545c-479e-a09c-f732f7e77413 1
 
< 0.1%
Other values (338084) 338084
> 99.9%
2025-01-08T17:42:40.036233image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 1690470
 
7.9%
6 1647936
 
7.7%
- 1352376
 
6.3%
t 1352376
 
6.3%
5 1309841
 
6.1%
a 1056185
 
5.0%
4 972781
 
4.6%
3 972418
 
4.6%
2 971788
 
4.6%
e 970508
 
4.6%
Other values (16) 9003243
42.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9213538
43.3%
Lowercase Letter 8029256
37.7%
Other Punctuation 2704752
 
12.7%
Dash Punctuation 1352376
 
6.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 1352376
16.8%
a 1056185
13.2%
e 970508
12.1%
b 718089
8.9%
n 676188
8.4%
f 634963
7.9%
c 634809
7.9%
d 633762
7.9%
k 338094
 
4.2%
r 338094
 
4.2%
Other values (2) 676188
8.4%
Decimal Number
ValueCountFrequency (%)
6 1647936
17.9%
5 1309841
14.2%
4 972781
10.6%
3 972418
10.6%
2 971788
10.5%
9 718905
7.8%
8 717477
7.8%
0 634479
 
6.9%
1 633985
 
6.9%
7 633928
 
6.9%
Other Punctuation
ValueCountFrequency (%)
/ 1690470
62.5%
: 676188
 
25.0%
. 338094
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
- 1352376
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13270666
62.3%
Latin 8029256
37.7%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 1690470
12.7%
6 1647936
12.4%
- 1352376
10.2%
5 1309841
9.9%
4 972781
7.3%
3 972418
7.3%
2 971788
7.3%
9 718905
 
5.4%
8 717477
 
5.4%
: 676188
 
5.1%
Other values (4) 2240486
16.9%
Latin
ValueCountFrequency (%)
t 1352376
16.8%
a 1056185
13.2%
e 970508
12.1%
b 718089
8.9%
n 676188
8.4%
f 634963
7.9%
c 634809
7.9%
d 633762
7.9%
k 338094
 
4.2%
r 338094
 
4.2%
Other values (2) 676188
8.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21299922
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 1690470
 
7.9%
6 1647936
 
7.7%
- 1352376
 
6.3%
t 1352376
 
6.3%
5 1309841
 
6.1%
a 1056185
 
5.0%
4 972781
 
4.6%
3 972418
 
4.6%
2 971788
 
4.6%
e 970508
 
4.6%
Other values (16) 9003243
42.3%

catalogNumber
Text

Missing 

Distinct225831
Distinct (%)84.4%
Missing70677
Missing (%)20.9%
Memory size2.6 MiB
2025-01-08T17:42:40.302636image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length20
Mean length14.08573127
Min length9

Characters and Unicode

Total characters3766764
Distinct characters36
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique192785 ?
Unique (%)72.1%

Sample

1st rowUSNMENT00976719.2
2nd rowUSNM 1566725
3rd rowUSNM 1430312
4th rowUSNM 1477111
5th rowUSNMENT01646520
ValueCountFrequency (%)
usnm 146196
33.4%
herp 7474
 
1.7%
tissue 7183
 
1.6%
us 2191
 
0.5%
2187
 
0.5%
lot 2187
 
0.5%
wet 2187
 
0.5%
image 291
 
0.1%
594492 64
 
< 0.1%
1487948 58
 
< 0.1%
Other values (223433) 267295
61.1%
2025-01-08T17:42:40.603909image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 384256
 
10.2%
1 338698
 
9.0%
0 282088
 
7.5%
S 267418
 
7.1%
U 267417
 
7.1%
M 265226
 
7.0%
4 250702
 
6.7%
6 201321
 
5.3%
3 187391
 
5.0%
2 174893
 
4.6%
Other values (26) 1147354
30.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1989649
52.8%
Uppercase Letter 1437341
38.2%
Space Separator 169896
 
4.5%
Other Punctuation 95068
 
2.5%
Lowercase Letter 72623
 
1.9%
Dash Punctuation 2187
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 17135
23.6%
s 14366
19.8%
p 7474
10.3%
r 7474
10.3%
i 7183
9.9%
u 7183
9.9%
t 4374
 
6.0%
w 2187
 
3.0%
l 2187
 
3.0%
o 2187
 
3.0%
Other values (3) 873
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
N 384256
26.7%
S 267418
18.6%
U 267417
18.6%
M 265226
18.5%
T 126214
 
8.8%
E 119030
 
8.3%
H 7474
 
0.5%
I 291
 
< 0.1%
A 14
 
< 0.1%
R 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 338698
17.0%
0 282088
14.2%
4 250702
12.6%
6 201321
10.1%
3 187391
9.4%
2 174893
8.8%
5 167336
8.4%
9 130800
 
6.6%
7 128397
 
6.5%
8 128023
 
6.4%
Space Separator
ValueCountFrequency (%)
169896
100.0%
Other Punctuation
ValueCountFrequency (%)
. 95068
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2187
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2256800
59.9%
Latin 1509964
40.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 384256
25.4%
S 267418
17.7%
U 267417
17.7%
M 265226
17.6%
T 126214
 
8.4%
E 119030
 
7.9%
e 17135
 
1.1%
s 14366
 
1.0%
p 7474
 
0.5%
r 7474
 
0.5%
Other values (13) 33954
 
2.2%
Common
ValueCountFrequency (%)
1 338698
15.0%
0 282088
12.5%
4 250702
11.1%
6 201321
8.9%
3 187391
8.3%
2 174893
7.7%
169896
7.5%
5 167336
7.4%
9 130800
 
5.8%
7 128397
 
5.7%
Other values (3) 225278
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3766764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 384256
 
10.2%
1 338698
 
9.0%
0 282088
 
7.5%
S 267418
 
7.1%
U 267417
 
7.1%
M 265226
 
7.0%
4 250702
 
6.7%
6 201321
 
5.3%
3 187391
 
5.0%
2 174893
 
4.6%
Other values (26) 1147354
30.5%

recordNumber
Text

Missing 

Distinct102948
Distinct (%)65.8%
Missing181582
Missing (%)53.7%
Memory size2.6 MiB
2025-01-08T17:42:40.761333image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length87
Median length53
Mean length8.259181405
Min length1

Characters and Unicode

Total characters1292661
Distinct characters76
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67344 ?
Unique (%)43.0%

Sample

1st rowT548-A9-TW19
2nd rowBMOO-09792
3rd rowJC3629
4th row707
5th rowmbio988
ValueCountFrequency (%)
blz 5367
 
2.9%
d&ml 4441
 
2.4%
1570
 
0.8%
tag 1340
 
0.7%
tree 1340
 
0.7%
flmoo 1323
 
0.7%
blb 1217
 
0.6%
sms 1215
 
0.6%
bah 989
 
0.5%
tob 834
 
0.4%
Other values (93496) 168604
89.6%
2025-01-08T17:42:40.982296image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 122723
 
9.5%
2 92650
 
7.2%
0 89200
 
6.9%
3 72330
 
5.6%
- 60851
 
4.7%
5 57939
 
4.5%
4 57585
 
4.5%
6 53715
 
4.2%
8 52782
 
4.1%
7 52215
 
4.0%
Other values (66) 580671
44.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 701177
54.2%
Uppercase Letter 421903
32.6%
Dash Punctuation 60866
 
4.7%
Lowercase Letter 41237
 
3.2%
Space Separator 31728
 
2.5%
Connector Punctuation 19931
 
1.5%
Other Punctuation 11779
 
0.9%
Close Punctuation 2020
 
0.2%
Open Punctuation 2020
 
0.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 37547
 
8.9%
B 36981
 
8.8%
O 31709
 
7.5%
M 31417
 
7.4%
S 27817
 
6.6%
A 26249
 
6.2%
R 24656
 
5.8%
T 22619
 
5.4%
L 20601
 
4.9%
E 18889
 
4.5%
Other values (16) 143418
34.0%
Lowercase Letter
ValueCountFrequency (%)
e 5194
12.6%
i 4265
10.3%
a 4119
10.0%
b 4004
9.7%
o 4001
9.7%
r 3388
8.2%
m 3332
8.1%
l 2843
6.9%
s 1665
 
4.0%
v 1558
 
3.8%
Other values (15) 6868
16.7%
Decimal Number
ValueCountFrequency (%)
1 122723
17.5%
2 92650
13.2%
0 89200
12.7%
3 72330
10.3%
5 57939
8.3%
4 57585
8.2%
6 53715
7.7%
8 52782
7.5%
7 52215
7.4%
9 50038
7.1%
Other Punctuation
ValueCountFrequency (%)
, 4691
39.8%
& 4583
38.9%
# 1512
 
12.8%
. 919
 
7.8%
/ 49
 
0.4%
? 22
 
0.2%
: 3
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 60851
> 99.9%
15
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 2006
99.3%
] 14
 
0.7%
Open Punctuation
ValueCountFrequency (%)
( 2006
99.3%
[ 14
 
0.7%
Space Separator
ValueCountFrequency (%)
31728
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 19931
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 829521
64.2%
Latin 463140
35.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 37547
 
8.1%
B 36981
 
8.0%
O 31709
 
6.8%
M 31417
 
6.8%
S 27817
 
6.0%
A 26249
 
5.7%
R 24656
 
5.3%
T 22619
 
4.9%
L 20601
 
4.4%
E 18889
 
4.1%
Other values (41) 184655
39.9%
Common
ValueCountFrequency (%)
1 122723
14.8%
2 92650
11.2%
0 89200
10.8%
3 72330
8.7%
- 60851
7.3%
5 57939
7.0%
4 57585
6.9%
6 53715
6.5%
8 52782
6.4%
7 52215
6.3%
Other values (15) 117531
14.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1292646
> 99.9%
Punctuation 15
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 122723
 
9.5%
2 92650
 
7.2%
0 89200
 
6.9%
3 72330
 
5.6%
- 60851
 
4.7%
5 57939
 
4.5%
4 57585
 
4.5%
6 53715
 
4.2%
8 52782
 
4.1%
7 52215
 
4.0%
Other values (65) 580656
44.9%
Punctuation
ValueCountFrequency (%)
15
100.0%

recordedBy
Text

Missing 

Distinct8090
Distinct (%)3.0%
Missing70120
Missing (%)20.7%
Memory size2.6 MiB
2025-01-08T17:42:41.156690image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length161
Median length107
Mean length24.15374253
Min length1

Characters and Unicode

Total characters6472575
Distinct characters83
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique912 ?
Unique (%)0.3%

Sample

1st rowR. Wielgus
2nd rowR. Vrijenhoek
3rd rowS. McPherson
4th rowK. Crandall, H. Robinson, J. Buhay & A. Toon
5th rowTibet-MacArthur, D. A. Bell, V. A. Funk, S. Ge, Y. Meng, Z. Nie, R. Ree, J. Wen, J. Yue & W. Zuo
ValueCountFrequency (%)
115458
 
8.9%
m 70969
 
5.5%
j 68929
 
5.3%
r 47195
 
3.6%
d 44002
 
3.4%
c 43587
 
3.4%
s 40805
 
3.1%
k 35410
 
2.7%
l 29135
 
2.2%
a 28392
 
2.2%
Other values (5513) 775991
59.7%
2025-01-08T17:42:41.519263image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1031899
15.9%
. 564920
 
8.7%
e 432034
 
6.7%
a 359856
 
5.6%
n 295498
 
4.6%
r 285565
 
4.4%
i 278605
 
4.3%
l 261098
 
4.0%
o 258914
 
4.0%
t 195845
 
3.0%
Other values (73) 2508341
38.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3375202
52.1%
Uppercase Letter 1202334
 
18.6%
Space Separator 1031899
 
15.9%
Other Punctuation 838090
 
12.9%
Dash Punctuation 13922
 
0.2%
Decimal Number 8798
 
0.1%
Close Punctuation 1220
 
< 0.1%
Open Punctuation 1110
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 432034
12.8%
a 359856
10.7%
n 295498
8.8%
r 285565
8.5%
i 278605
 
8.3%
l 261098
 
7.7%
o 258914
 
7.7%
t 195845
 
5.8%
s 188962
 
5.6%
u 120782
 
3.6%
Other values (27) 698043
20.7%
Uppercase Letter
ValueCountFrequency (%)
M 124557
 
10.4%
S 91413
 
7.6%
C 84834
 
7.1%
B 82834
 
6.9%
R 80131
 
6.7%
J 77045
 
6.4%
P 76310
 
6.3%
D 68047
 
5.7%
L 65318
 
5.4%
W 57241
 
4.8%
Other values (17) 394604
32.8%
Decimal Number
ValueCountFrequency (%)
9 2228
25.3%
1 2076
23.6%
2 2014
22.9%
0 1930
21.9%
8 370
 
4.2%
6 94
 
1.1%
4 84
 
1.0%
3 2
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 564920
67.4%
, 154997
 
18.5%
& 115454
 
13.8%
/ 2045
 
0.2%
' 674
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 1010
82.8%
] 210
 
17.2%
Open Punctuation
ValueCountFrequency (%)
( 900
81.1%
[ 210
 
18.9%
Space Separator
ValueCountFrequency (%)
1031899
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13922
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4577536
70.7%
Common 1895039
29.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 432034
 
9.4%
a 359856
 
7.9%
n 295498
 
6.5%
r 285565
 
6.2%
i 278605
 
6.1%
l 261098
 
5.7%
o 258914
 
5.7%
t 195845
 
4.3%
s 188962
 
4.1%
M 124557
 
2.7%
Other values (54) 1896602
41.4%
Common
ValueCountFrequency (%)
1031899
54.5%
. 564920
29.8%
, 154997
 
8.2%
& 115454
 
6.1%
- 13922
 
0.7%
9 2228
 
0.1%
1 2076
 
0.1%
/ 2045
 
0.1%
2 2014
 
0.1%
0 1930
 
0.1%
Other values (9) 3554
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6470585
> 99.9%
None 1990
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1031899
15.9%
. 564920
 
8.7%
e 432034
 
6.7%
a 359856
 
5.6%
n 295498
 
4.6%
r 285565
 
4.4%
i 278605
 
4.3%
l 261098
 
4.0%
o 258914
 
4.0%
t 195845
 
3.0%
Other values (61) 2506351
38.7%
None
ValueCountFrequency (%)
í 1006
50.6%
é 487
24.5%
ö 156
 
7.8%
á 138
 
6.9%
ó 97
 
4.9%
Ç 33
 
1.7%
ı 33
 
1.7%
ñ 21
 
1.1%
ú 12
 
0.6%
ü 3
 
0.2%
Other values (2) 4
 
0.2%

individualCount
Text

Missing 

Distinct19
Distinct (%)< 0.1%
Missing39347
Missing (%)11.6%
Memory size2.6 MiB
2025-01-08T17:42:41.577032image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.000127198
Min length1

Characters and Unicode

Total characters298785
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 294711
98.6%
0 2658
 
0.9%
4 440
 
0.1%
2 363
 
0.1%
5 280
 
0.1%
3 226
 
0.1%
10 26
 
< 0.1%
6 20
 
< 0.1%
8 5
 
< 0.1%
7 4
 
< 0.1%
Other values (9) 14
 
< 0.1%
2025-01-08T17:42:41.671551image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 294745
98.6%
0 2688
 
0.9%
4 442
 
0.1%
2 368
 
0.1%
5 280
 
0.1%
3 229
 
0.1%
6 21
 
< 0.1%
8 5
 
< 0.1%
7 4
 
< 0.1%
9 3
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 298785
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 294745
98.6%
0 2688
 
0.9%
4 442
 
0.1%
2 368
 
0.1%
5 280
 
0.1%
3 229
 
0.1%
6 21
 
< 0.1%
8 5
 
< 0.1%
7 4
 
< 0.1%
9 3
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 298785
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 294745
98.6%
0 2688
 
0.9%
4 442
 
0.1%
2 368
 
0.1%
5 280
 
0.1%
3 229
 
0.1%
6 21
 
< 0.1%
8 5
 
< 0.1%
7 4
 
< 0.1%
9 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 298785
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 294745
98.6%
0 2688
 
0.9%
4 442
 
0.1%
2 368
 
0.1%
5 280
 
0.1%
3 229
 
0.1%
6 21
 
< 0.1%
8 5
 
< 0.1%
7 4
 
< 0.1%
9 3
 
< 0.1%

sex
Text

Missing 

Distinct3
Distinct (%)< 0.1%
Missing265741
Missing (%)78.6%
Memory size2.6 MiB
2025-01-08T17:42:41.712216image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length4
Mean length4.888021229
Min length4

Characters and Unicode

Total characters353663
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMALE
2nd rowMALE
3rd rowMALE
4th rowFEMALE
5th rowMALE
ValueCountFrequency (%)
male 40483
56.0%
female 31797
43.9%
hermaphrodite 73
 
0.1%
2025-01-08T17:42:41.805815image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 104223
29.5%
M 72353
20.5%
A 72353
20.5%
L 72280
20.4%
F 31797
 
9.0%
H 146
 
< 0.1%
R 146
 
< 0.1%
P 73
 
< 0.1%
O 73
 
< 0.1%
D 73
 
< 0.1%
Other values (2) 146
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 353663
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 104223
29.5%
M 72353
20.5%
A 72353
20.5%
L 72280
20.4%
F 31797
 
9.0%
H 146
 
< 0.1%
R 146
 
< 0.1%
P 73
 
< 0.1%
O 73
 
< 0.1%
D 73
 
< 0.1%
Other values (2) 146
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 353663
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 104223
29.5%
M 72353
20.5%
A 72353
20.5%
L 72280
20.4%
F 31797
 
9.0%
H 146
 
< 0.1%
R 146
 
< 0.1%
P 73
 
< 0.1%
O 73
 
< 0.1%
D 73
 
< 0.1%
Other values (2) 146
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 353663
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 104223
29.5%
M 72353
20.5%
A 72353
20.5%
L 72280
20.4%
F 31797
 
9.0%
H 146
 
< 0.1%
R 146
 
< 0.1%
P 73
 
< 0.1%
O 73
 
< 0.1%
D 73
 
< 0.1%
Other values (2) 146
 
< 0.1%

lifeStage
Text

Missing 

Distinct25
Distinct (%)< 0.1%
Missing209004
Missing (%)61.8%
Memory size2.6 MiB
2025-01-08T17:42:41.854572image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length5
Mean length5.126787513
Min length3

Characters and Unicode

Total characters661817
Distinct characters38
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowAdult
2nd rowAdult
3rd rowAdult
4th rowAdult
5th rowAdult
ValueCountFrequency (%)
adult 120982
93.7%
juvenile 3007
 
2.3%
larva 1688
 
1.3%
flowering 959
 
0.7%
unknown 541
 
0.4%
subadult 513
 
0.4%
eft 308
 
0.2%
immature 251
 
0.2%
veliger 163
 
0.1%
fruiting 134
 
0.1%
Other values (15) 544
 
0.4%
2025-01-08T17:42:41.966009image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 125703
19.0%
u 125581
19.0%
t 122330
18.5%
d 121514
18.4%
A 120982
18.3%
e 7872
 
1.2%
n 5826
 
0.9%
v 4696
 
0.7%
a 4561
 
0.7%
i 4472
 
0.7%
Other values (28) 18280
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 532727
80.5%
Uppercase Letter 129090
 
19.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 125703
23.6%
u 125581
23.6%
t 122330
23.0%
d 121514
22.8%
e 7872
 
1.5%
n 5826
 
1.1%
v 4696
 
0.9%
a 4561
 
0.9%
i 4472
 
0.8%
r 3201
 
0.6%
Other values (12) 6971
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
A 120982
93.7%
J 3007
 
2.3%
L 1688
 
1.3%
F 1130
 
0.9%
U 541
 
0.4%
S 513
 
0.4%
E 377
 
0.3%
I 251
 
0.2%
V 164
 
0.1%
P 136
 
0.1%
Other values (6) 301
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 661817
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 125703
19.0%
u 125581
19.0%
t 122330
18.5%
d 121514
18.4%
A 120982
18.3%
e 7872
 
1.2%
n 5826
 
0.9%
v 4696
 
0.7%
a 4561
 
0.7%
i 4472
 
0.7%
Other values (28) 18280
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 661817
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 125703
19.0%
u 125581
19.0%
t 122330
18.5%
d 121514
18.4%
A 120982
18.3%
e 7872
 
1.2%
n 5826
 
0.9%
v 4696
 
0.7%
a 4561
 
0.7%
i 4472
 
0.7%
Other values (28) 18280
 
2.8%

occurrenceStatus
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
2025-01-08T17:42:42.008008image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters2366658
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPRESENT
2nd rowPRESENT
3rd rowPRESENT
4th rowPRESENT
5th rowPRESENT
ValueCountFrequency (%)
present 338094
100.0%
2025-01-08T17:42:42.096898image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 676188
28.6%
P 338094
14.3%
R 338094
14.3%
S 338094
14.3%
N 338094
14.3%
T 338094
14.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2366658
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 676188
28.6%
P 338094
14.3%
R 338094
14.3%
S 338094
14.3%
N 338094
14.3%
T 338094
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 2366658
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 676188
28.6%
P 338094
14.3%
R 338094
14.3%
S 338094
14.3%
N 338094
14.3%
T 338094
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2366658
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 676188
28.6%
P 338094
14.3%
R 338094
14.3%
S 338094
14.3%
N 338094
14.3%
T 338094
14.3%

preparations
Text

Missing 

Distinct34
Distinct (%)< 0.1%
Missing251111
Missing (%)74.3%
Memory size2.6 MiB
2025-01-08T17:42:42.144428image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length142
Median length6
Mean length6.19215249
Min length4

Characters and Unicode

Total characters538612
Distinct characters47
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st rowFrozen
2nd rowFrozen
3rd rowFrozen
4th rowFrozen
5th rowFrozen
ValueCountFrequency (%)
frozen 72559
79.3%
vial 6698
 
7.3%
ethanol 4918
 
5.4%
wet 2268
 
2.5%
lot 2268
 
2.5%
drained 1063
 
1.2%
photograph 626
 
0.7%
biorepository 456
 
0.5%
alcohol 197
 
0.2%
148
 
0.2%
Other values (11) 295
 
0.3%
2025-01-08T17:42:42.256909image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 82904
15.4%
n 78637
14.6%
e 76402
14.2%
r 75218
14.0%
z 72559
13.5%
F 72209
13.4%
l 14333
 
2.7%
a 13317
 
2.5%
t 10591
 
2.0%
i 8773
 
1.6%
Other values (37) 33669
6.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 447509
83.1%
Uppercase Letter 84882
 
15.8%
Space Separator 4513
 
0.8%
Other Punctuation 836
 
0.2%
Decimal Number 296
 
0.1%
Open Punctuation 197
 
< 0.1%
Close Punctuation 197
 
< 0.1%
Dash Punctuation 182
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 82904
18.5%
n 78637
17.6%
e 76402
17.1%
r 75218
16.8%
z 72559
16.2%
l 14333
 
3.2%
a 13317
 
3.0%
t 10591
 
2.4%
i 8773
 
2.0%
h 6367
 
1.4%
Other values (13) 8408
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
F 72209
85.1%
E 4953
 
5.8%
V 3863
 
4.6%
W 2253
 
2.7%
P 626
 
0.7%
B 456
 
0.5%
A 242
 
0.3%
D 73
 
0.1%
L 49
 
0.1%
S 37
 
< 0.1%
Other values (5) 121
 
0.1%
Other Punctuation
ValueCountFrequency (%)
; 640
76.6%
% 148
 
17.7%
' 48
 
5.7%
Decimal Number
ValueCountFrequency (%)
9 148
50.0%
5 148
50.0%
Space Separator
ValueCountFrequency (%)
4513
100.0%
Open Punctuation
ValueCountFrequency (%)
( 197
100.0%
Close Punctuation
ValueCountFrequency (%)
) 197
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 182
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 532391
98.8%
Common 6221
 
1.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 82904
15.6%
n 78637
14.8%
e 76402
14.4%
r 75218
14.1%
z 72559
13.6%
F 72209
13.6%
l 14333
 
2.7%
a 13317
 
2.5%
t 10591
 
2.0%
i 8773
 
1.6%
Other values (28) 27448
 
5.2%
Common
ValueCountFrequency (%)
4513
72.5%
; 640
 
10.3%
( 197
 
3.2%
) 197
 
3.2%
- 182
 
2.9%
9 148
 
2.4%
% 148
 
2.4%
5 148
 
2.4%
' 48
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 538612
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 82904
15.4%
n 78637
14.6%
e 76402
14.2%
r 75218
14.0%
z 72559
13.5%
F 72209
13.4%
l 14333
 
2.7%
a 13317
 
2.5%
t 10591
 
2.0%
i 8773
 
1.6%
Other values (37) 33669
6.3%
Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
2025-01-08T17:42:42.300387image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length12.38328985
Min length2

Characters and Unicode

Total characters4186716
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowin collection
2nd rowin collection
3rd rowin collection
4th rowin collection
5th rowin collection
ValueCountFrequency (%)
in 298321
46.9%
collection 298321
46.9%
consumed 38009
 
6.0%
yes 943
 
0.1%
no 821
 
0.1%
2025-01-08T17:42:42.395850image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 635472
15.2%
o 635472
15.2%
c 634651
15.2%
i 596642
14.3%
l 596642
14.3%
e 337273
8.1%
298321
7.1%
t 298321
7.1%
s 38952
 
0.9%
u 38009
 
0.9%
Other values (3) 76961
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3888395
92.9%
Space Separator 298321
 
7.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 635472
16.3%
o 635472
16.3%
c 634651
16.3%
i 596642
15.3%
l 596642
15.3%
e 337273
8.7%
t 298321
7.7%
s 38952
 
1.0%
u 38009
 
1.0%
m 38009
 
1.0%
Other values (2) 38952
 
1.0%
Space Separator
ValueCountFrequency (%)
298321
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3888395
92.9%
Common 298321
 
7.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 635472
16.3%
o 635472
16.3%
c 634651
16.3%
i 596642
15.3%
l 596642
15.3%
e 337273
8.7%
t 298321
7.7%
s 38952
 
1.0%
u 38009
 
1.0%
m 38009
 
1.0%
Other values (2) 38952
 
1.0%
Common
ValueCountFrequency (%)
298321
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4186716
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 635472
15.2%
o 635472
15.2%
c 634651
15.2%
i 596642
14.3%
l 596642
14.3%
e 337273
8.1%
298321
7.1%
t 298321
7.1%
s 38952
 
0.9%
u 38009
 
0.9%
Other values (3) 76961
 
1.8%

associatedSequences
Text

Missing 

Distinct25139
Distinct (%)76.9%
Missing305424
Missing (%)90.3%
Memory size2.6 MiB
2025-01-08T17:42:42.599972image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length206
Median length8
Mean length11.03008877
Min length8

Characters and Unicode

Total characters360353
Distinct characters34
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17608 ?
Unique (%)53.9%

Sample

1st rowMW204230;MW124559
2nd rowMW982336
3rd rowMF785606;MF785913
4th rowMN344605
5th rowJQ840329
ValueCountFrequency (%)
mw983728 2
 
< 0.1%
mg967848 2
 
< 0.1%
mn344832 2
 
< 0.1%
mw984278 2
 
< 0.1%
mn345511 2
 
< 0.1%
mw277828 2
 
< 0.1%
mn344810 2
 
< 0.1%
kt733332 2
 
< 0.1%
mw277965 2
 
< 0.1%
mg968024 2
 
< 0.1%
Other values (25129) 32650
99.9%
2025-01-08T17:42:42.872368image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 34014
 
9.4%
3 32561
 
9.0%
4 30927
 
8.6%
9 27656
 
7.7%
M 27232
 
7.6%
2 27065
 
7.5%
7 23931
 
6.6%
0 23180
 
6.4%
5 21355
 
5.9%
1 21111
 
5.9%
Other values (24) 91321
25.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 261882
72.7%
Uppercase Letter 87721
 
24.3%
Other Punctuation 10750
 
3.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 27232
31.0%
W 9690
 
11.0%
O 9358
 
10.7%
Q 7270
 
8.3%
N 6092
 
6.9%
F 4770
 
5.4%
J 4063
 
4.6%
H 3581
 
4.1%
K 3129
 
3.6%
P 2661
 
3.0%
Other values (11) 9875
 
11.3%
Decimal Number
ValueCountFrequency (%)
8 34014
13.0%
3 32561
12.4%
4 30927
11.8%
9 27656
10.6%
2 27065
10.3%
7 23931
9.1%
0 23180
8.9%
5 21355
8.2%
1 21111
8.1%
6 20082
7.7%
Other Punctuation
ValueCountFrequency (%)
; 10748
> 99.9%
/ 1
 
< 0.1%
. 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 272632
75.7%
Latin 87721
 
24.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 27232
31.0%
W 9690
 
11.0%
O 9358
 
10.7%
Q 7270
 
8.3%
N 6092
 
6.9%
F 4770
 
5.4%
J 4063
 
4.6%
H 3581
 
4.1%
K 3129
 
3.6%
P 2661
 
3.0%
Other values (11) 9875
 
11.3%
Common
ValueCountFrequency (%)
8 34014
12.5%
3 32561
11.9%
4 30927
11.3%
9 27656
10.1%
2 27065
9.9%
7 23931
8.8%
0 23180
8.5%
5 21355
7.8%
1 21111
7.7%
6 20082
7.4%
Other values (3) 10750
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 360353
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 34014
 
9.4%
3 32561
 
9.0%
4 30927
 
8.6%
9 27656
 
7.7%
M 27232
 
7.6%
2 27065
 
7.5%
7 23931
 
6.6%
0 23180
 
6.4%
5 21355
 
5.9%
1 21111
 
5.9%
Other values (24) 91321
25.3%

occurrenceRemarks
Text

Missing 

Distinct28684
Distinct (%)19.8%
Missing193547
Missing (%)57.2%
Memory size2.6 MiB
2025-01-08T17:42:43.073880image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length282633
Median length61
Mean length83.85489841
Min length1

Characters and Unicode

Total characters12120974
Distinct characters130
Distinct categories14 ?
Distinct scripts2 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19947 ?
Unique (%)13.8%

Sample

1st rowOne leg removed for genetic sampling while on loan to GUELPH.
2nd rowOrder: 10948; Box Number: MBARI_0136: Box Position: B/4
3rd rowOne leg removed for genetic sampling while on loan to GUELPH.
4th rowOriginally cataloged as an image record because field notes indicated there was a photovoucher for the specimen. When the images were cataloged in early 2020, no photos were found for this specimen so the record was changed to a Genetic Sample (DNA) with no voucher.
5th rowEntire tissue sample consumed for DNA extraction. Specimen voucher located at Museum National d'Histoire Naturelle, Paris.
ValueCountFrequency (%)
for 114846
 
5.9%
on 113429
 
5.8%
to 111972
 
5.7%
genetic 110770
 
5.7%
while 109786
 
5.6%
sampling 108913
 
5.6%
loan 108870
 
5.6%
removed 108857
 
5.6%
guelph 108797
 
5.6%
one 105620
 
5.4%
Other values (46309) 846419
43.4%
2025-01-08T17:42:43.332650image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1744442
 
14.4%
e 1113548
 
9.2%
o 806325
 
6.7%
n 721471
 
6.0%
l 597748
 
4.9%
i 588547
 
4.9%
a 470216
 
3.9%
t 429603
 
3.5%
r 425976
 
3.5%
g 361714
 
3.0%
Other values (120) 4861384
40.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7502487
61.9%
Space Separator 1744442
 
14.4%
Uppercase Letter 1548802
 
12.8%
Decimal Number 633553
 
5.2%
Other Punctuation 420227
 
3.5%
Control 177159
 
1.5%
Dash Punctuation 41131
 
0.3%
Connector Punctuation 24577
 
0.2%
Math Symbol 18238
 
0.2%
Open Punctuation 5170
 
< 0.1%
Other values (4) 5188
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1113548
14.8%
o 806325
10.7%
n 721471
9.6%
l 597748
 
8.0%
i 588547
 
7.8%
a 470216
 
6.3%
t 429603
 
5.7%
r 425976
 
5.7%
g 361714
 
4.8%
m 297830
 
4.0%
Other values (44) 1689509
22.5%
Uppercase Letter
ValueCountFrequency (%)
P 148874
9.6%
O 145398
 
9.4%
G 142014
 
9.2%
E 136146
 
8.8%
U 129096
 
8.3%
H 128358
 
8.3%
L 121543
 
7.8%
N 77084
 
5.0%
B 75895
 
4.9%
M 72763
 
4.7%
Other values (20) 371631
24.0%
Other Punctuation
ValueCountFrequency (%)
. 182353
43.4%
: 91346
21.7%
; 73034
17.4%
, 40116
 
9.5%
/ 22748
 
5.4%
' 3166
 
0.8%
" 3111
 
0.7%
# 2404
 
0.6%
& 1284
 
0.3%
? 550
 
0.1%
Other values (4) 115
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 116594
18.4%
0 94063
14.8%
2 75391
11.9%
9 57354
9.1%
3 52443
8.3%
4 50558
8.0%
8 47354
7.5%
7 47090
7.4%
5 46487
 
7.3%
6 46219
 
7.3%
Math Symbol
ValueCountFrequency (%)
| 17759
97.4%
= 377
 
2.1%
+ 59
 
0.3%
~ 17
 
0.1%
< 16
 
0.1%
> 10
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 4350
84.2%
] 809
 
15.7%
} 6
 
0.1%
Other Symbol
ValueCountFrequency (%)
° 12
57.1%
5
23.8%
4
 
19.0%
Control
ValueCountFrequency (%)
176366
99.6%
793
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
- 40888
99.4%
243
 
0.6%
Open Punctuation
ValueCountFrequency (%)
( 4358
84.3%
[ 812
 
15.7%
Space Separator
ValueCountFrequency (%)
1744442
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 24577
100.0%
Final Punctuation
ValueCountFrequency (%)
» 1
100.0%
Currency Symbol
ValueCountFrequency (%)
¢ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9051277
74.7%
Common 3069697
 
25.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1113548
 
12.3%
o 806325
 
8.9%
n 721471
 
8.0%
l 597748
 
6.6%
i 588547
 
6.5%
a 470216
 
5.2%
t 429603
 
4.7%
r 425976
 
4.7%
g 361714
 
4.0%
m 297830
 
3.3%
Other values (73) 3238299
35.8%
Common
ValueCountFrequency (%)
1744442
56.8%
. 182353
 
5.9%
176366
 
5.7%
1 116594
 
3.8%
0 94063
 
3.1%
: 91346
 
3.0%
2 75391
 
2.5%
; 73034
 
2.4%
9 57354
 
1.9%
3 52443
 
1.7%
Other values (37) 406311
 
13.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12120332
> 99.9%
None 386
 
< 0.1%
Punctuation 243
 
< 0.1%
Misc Symbols 9
 
< 0.1%
Latin Ext Additional 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1744442
 
14.4%
e 1113548
 
9.2%
o 806325
 
6.7%
n 721471
 
6.0%
l 597748
 
4.9%
i 588547
 
4.9%
a 470216
 
3.9%
t 429603
 
3.5%
r 425976
 
3.5%
g 361714
 
3.0%
Other values (81) 4860742
40.1%
Punctuation
ValueCountFrequency (%)
243
100.0%
None
ValueCountFrequency (%)
é 109
28.2%
í 41
 
10.6%
ü 36
 
9.3%
ã 29
 
7.5%
Î 27
 
7.0%
ó 19
 
4.9%
á 16
 
4.1%
è 15
 
3.9%
µ 12
 
3.1%
° 12
 
3.1%
Other values (22) 70
18.1%
Misc Symbols
ValueCountFrequency (%)
5
55.6%
4
44.4%
Latin Ext Additional
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

organismName
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing338093
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:43.380650image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowEML
ValueCountFrequency (%)
eml 1
100.0%
2025-01-08T17:42:43.468162image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 1
33.3%
M 1
33.3%
L 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 1
33.3%
M 1
33.3%
L 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 3
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 1
33.3%
M 1
33.3%
L 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 1
33.3%
M 1
33.3%
L 1
33.3%

organismScope
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing338093
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:43.519162image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters24
Distinct characters12
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row2024-12-01T12:07:33.811Z
ValueCountFrequency (%)
2024-12-01t12:07:33.811z 1
100.0%
2025-01-08T17:42:43.614898image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5
20.8%
2 4
16.7%
0 3
12.5%
- 2
 
8.3%
: 2
 
8.3%
3 2
 
8.3%
4 1
 
4.2%
T 1
 
4.2%
7 1
 
4.2%
. 1
 
4.2%
Other values (2) 2
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17
70.8%
Other Punctuation 3
 
12.5%
Dash Punctuation 2
 
8.3%
Uppercase Letter 2
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5
29.4%
2 4
23.5%
0 3
17.6%
3 2
 
11.8%
4 1
 
5.9%
7 1
 
5.9%
8 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
: 2
66.7%
. 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
Z 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22
91.7%
Latin 2
 
8.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 5
22.7%
2 4
18.2%
0 3
13.6%
- 2
 
9.1%
: 2
 
9.1%
3 2
 
9.1%
4 1
 
4.5%
7 1
 
4.5%
. 1
 
4.5%
8 1
 
4.5%
Latin
ValueCountFrequency (%)
T 1
50.0%
Z 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5
20.8%
2 4
16.7%
0 3
12.5%
- 2
 
8.3%
: 2
 
8.3%
3 2
 
8.3%
4 1
 
4.2%
T 1
 
4.2%
7 1
 
4.2%
. 1
 
4.2%
Other values (2) 2
 
8.3%

associatedOrganisms
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing338093
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:43.662170image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters24
Distinct characters10
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row2024-12-01T11:07:21.711Z
ValueCountFrequency (%)
2024-12-01t11:07:21.711z 1
100.0%
2025-01-08T17:42:43.754291image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7
29.2%
2 4
16.7%
0 3
12.5%
- 2
 
8.3%
: 2
 
8.3%
7 2
 
8.3%
4 1
 
4.2%
T 1
 
4.2%
. 1
 
4.2%
Z 1
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17
70.8%
Other Punctuation 3
 
12.5%
Dash Punctuation 2
 
8.3%
Uppercase Letter 2
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7
41.2%
2 4
23.5%
0 3
17.6%
7 2
 
11.8%
4 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
: 2
66.7%
. 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
Z 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22
91.7%
Latin 2
 
8.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7
31.8%
2 4
18.2%
0 3
13.6%
- 2
 
9.1%
: 2
 
9.1%
7 2
 
9.1%
4 1
 
4.5%
. 1
 
4.5%
Latin
ValueCountFrequency (%)
T 1
50.0%
Z 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7
29.2%
2 4
16.7%
0 3
12.5%
- 2
 
8.3%
: 2
 
8.3%
7 2
 
8.3%
4 1
 
4.2%
T 1
 
4.2%
. 1
 
4.2%
Z 1
 
4.2%

previousIdentifications
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing338093
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:43.794291image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowtrue
ValueCountFrequency (%)
true 1
100.0%
2025-01-08T17:42:43.880031image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 1
25.0%
r 1
25.0%
u 1
25.0%
e 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 1
25.0%
r 1
25.0%
u 1
25.0%
e 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 1
25.0%
r 1
25.0%
u 1
25.0%
e 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 1
25.0%
r 1
25.0%
u 1
25.0%
e 1
25.0%

materialEntityRemarks
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing338093
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:43.919101image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowfalse
ValueCountFrequency (%)
false 1
100.0%
2025-01-08T17:42:44.007599image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
f 1
20.0%
a 1
20.0%
l 1
20.0%
s 1
20.0%
e 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
f 1
20.0%
a 1
20.0%
l 1
20.0%
s 1
20.0%
e 1
20.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
f 1
20.0%
a 1
20.0%
l 1
20.0%
s 1
20.0%
e 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
f 1
20.0%
a 1
20.0%
l 1
20.0%
s 1
20.0%
e 1
20.0%

verbatimLabel
Text

Missing 

Distinct5
Distinct (%)100.0%
Missing338089
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:44.054833image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length7
Mean length8
Min length6

Characters and Unicode

Total characters40
Distinct characters21
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row10.6925
2nd row5.55461
3rd rowLATIN_AMERICA
4th row7.1633
5th row5.80961
ValueCountFrequency (%)
10.6925 1
20.0%
5.55461 1
20.0%
latin_america 1
20.0%
7.1633 1
20.0%
5.80961 1
20.0%
2025-01-08T17:42:44.157038image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 5
12.5%
1 4
 
10.0%
. 4
 
10.0%
6 4
 
10.0%
A 3
 
7.5%
9 2
 
5.0%
3 2
 
5.0%
0 2
 
5.0%
I 2
 
5.0%
M 1
 
2.5%
Other values (11) 11
27.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23
57.5%
Uppercase Letter 12
30.0%
Other Punctuation 4
 
10.0%
Connector Punctuation 1
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 5
21.7%
1 4
17.4%
6 4
17.4%
9 2
 
8.7%
3 2
 
8.7%
0 2
 
8.7%
7 1
 
4.3%
4 1
 
4.3%
2 1
 
4.3%
8 1
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
A 3
25.0%
I 2
16.7%
M 1
 
8.3%
C 1
 
8.3%
R 1
 
8.3%
E 1
 
8.3%
T 1
 
8.3%
N 1
 
8.3%
L 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 28
70.0%
Latin 12
30.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 5
17.9%
1 4
14.3%
. 4
14.3%
6 4
14.3%
9 2
 
7.1%
3 2
 
7.1%
0 2
 
7.1%
7 1
 
3.6%
_ 1
 
3.6%
4 1
 
3.6%
Other values (2) 2
 
7.1%
Latin
ValueCountFrequency (%)
A 3
25.0%
I 2
16.7%
M 1
 
8.3%
C 1
 
8.3%
R 1
 
8.3%
E 1
 
8.3%
T 1
 
8.3%
N 1
 
8.3%
L 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 5
12.5%
1 4
 
10.0%
. 4
 
10.0%
6 4
 
10.0%
A 3
 
7.5%
9 2
 
5.0%
3 2
 
5.0%
0 2
 
5.0%
I 2
 
5.0%
M 1
 
2.5%
Other values (11) 11
27.5%

materialSampleID
Text

Missing 

Distinct253108
Distinct (%)100.0%
Missing84986
Missing (%)25.1%
Memory size2.6 MiB
2025-01-08T17:42:44.430328image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length7
Mean length7.000031607
Min length7

Characters and Unicode

Total characters1771764
Distinct characters39
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique253108 ?
Unique (%)100.0%

Sample

1st rowAR5TC43
2nd rowAL2IC84
3rd rowAF9HI08
4th rowAD5JZ99
5th rowAE0OQ35
ValueCountFrequency (%)
ar5tc43 1
 
< 0.1%
ae3rz90 1
 
< 0.1%
am1rc30 1
 
< 0.1%
al7ng44 1
 
< 0.1%
an9jb30 1
 
< 0.1%
af9hi08 1
 
< 0.1%
ad5jz99 1
 
< 0.1%
ae0oq35 1
 
< 0.1%
an7hd65 1
 
< 0.1%
ak3zy87 1
 
< 0.1%
Other values (253098) 253098
> 99.9%
2025-01-08T17:42:44.769020image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 287625
 
16.2%
7 79818
 
4.5%
1 77867
 
4.4%
2 77272
 
4.4%
0 77025
 
4.3%
4 76603
 
4.3%
5 76332
 
4.3%
3 76014
 
4.3%
9 74989
 
4.2%
6 73630
 
4.2%
Other values (29) 794589
44.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1012424
57.1%
Decimal Number 759333
42.9%
Other Punctuation 4
 
< 0.1%
Dash Punctuation 2
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 287625
28.4%
O 39928
 
3.9%
R 39126
 
3.9%
K 38842
 
3.8%
E 36151
 
3.6%
C 35388
 
3.5%
L 34783
 
3.4%
H 34197
 
3.4%
I 33715
 
3.3%
F 33659
 
3.3%
Other values (16) 399010
39.4%
Decimal Number
ValueCountFrequency (%)
7 79818
10.5%
1 77867
10.3%
2 77272
10.2%
0 77025
10.1%
4 76603
10.1%
5 76332
10.1%
3 76014
10.0%
9 74989
9.9%
6 73630
9.7%
8 69783
9.2%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1012424
57.1%
Common 759340
42.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 287625
28.4%
O 39928
 
3.9%
R 39126
 
3.9%
K 38842
 
3.8%
E 36151
 
3.6%
C 35388
 
3.5%
L 34783
 
3.4%
H 34197
 
3.4%
I 33715
 
3.3%
F 33659
 
3.3%
Other values (16) 399010
39.4%
Common
ValueCountFrequency (%)
7 79818
10.5%
1 77867
10.3%
2 77272
10.2%
0 77025
10.1%
4 76603
10.1%
5 76332
10.1%
3 76014
10.0%
9 74989
9.9%
6 73630
9.7%
8 69783
9.2%
Other values (3) 7
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1771764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 287625
 
16.2%
7 79818
 
4.5%
1 77867
 
4.4%
2 77272
 
4.4%
0 77025
 
4.3%
4 76603
 
4.3%
5 76332
 
4.3%
3 76014
 
4.3%
9 74989
 
4.2%
6 73630
 
4.2%
Other values (29) 794589
44.8%

eventID
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing338092
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:44.823087image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5
Min length3

Characters and Unicode

Total characters10
Distinct characters9
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row94648.0
2nd rowPAN
ValueCountFrequency (%)
94648.0 1
50.0%
pan 1
50.0%
2025-01-08T17:42:44.922956image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 2
20.0%
9 1
10.0%
6 1
10.0%
8 1
10.0%
. 1
10.0%
0 1
10.0%
P 1
10.0%
A 1
10.0%
N 1
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
60.0%
Uppercase Letter 3
30.0%
Other Punctuation 1
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 2
33.3%
9 1
16.7%
6 1
16.7%
8 1
16.7%
0 1
16.7%
Uppercase Letter
ValueCountFrequency (%)
P 1
33.3%
A 1
33.3%
N 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7
70.0%
Latin 3
30.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 2
28.6%
9 1
14.3%
6 1
14.3%
8 1
14.3%
. 1
14.3%
0 1
14.3%
Latin
ValueCountFrequency (%)
P 1
33.3%
A 1
33.3%
N 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 2
20.0%
9 1
10.0%
6 1
10.0%
8 1
10.0%
. 1
10.0%
0 1
10.0%
P 1
10.0%
A 1
10.0%
N 1
10.0%

parentEventID
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing338093
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:44.963956image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowPanama
ValueCountFrequency (%)
panama 1
100.0%
2025-01-08T17:42:45.050531image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 3
50.0%
P 1
 
16.7%
n 1
 
16.7%
m 1
 
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5
83.3%
Uppercase Letter 1
 
16.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 3
60.0%
n 1
 
20.0%
m 1
 
20.0%
Uppercase Letter
ValueCountFrequency (%)
P 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 3
50.0%
P 1
 
16.7%
n 1
 
16.7%
m 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 3
50.0%
P 1
 
16.7%
n 1
 
16.7%
m 1
 
16.7%

eventType
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing338093
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:45.089530image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters7
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowPAN.5_1
ValueCountFrequency (%)
pan.5_1 1
100.0%
2025-01-08T17:42:45.178487image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
P 1
14.3%
A 1
14.3%
N 1
14.3%
. 1
14.3%
5 1
14.3%
_ 1
14.3%
1 1
14.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3
42.9%
Decimal Number 2
28.6%
Other Punctuation 1
 
14.3%
Connector Punctuation 1
 
14.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
P 1
33.3%
A 1
33.3%
N 1
33.3%
Decimal Number
ValueCountFrequency (%)
5 1
50.0%
1 1
50.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
57.1%
Latin 3
42.9%

Most frequent character per script

Common
ValueCountFrequency (%)
. 1
25.0%
5 1
25.0%
_ 1
25.0%
1 1
25.0%
Latin
ValueCountFrequency (%)
P 1
33.3%
A 1
33.3%
N 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P 1
14.3%
A 1
14.3%
N 1
14.3%
. 1
14.3%
5 1
14.3%
_ 1
14.3%
1 1
14.3%

fieldNumber
Text

Missing 

Distinct7065
Distinct (%)10.0%
Missing267153
Missing (%)79.0%
Memory size2.6 MiB
2025-01-08T17:42:45.346990image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length56
Median length43
Mean length11.55329076
Min length1

Characters and Unicode

Total characters819602
Distinct characters73
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2664 ?
Unique (%)3.8%

Sample

1st rowMBARI/T548
2nd rowMBIO/BIZ-231
3rd rowMoorea F-06-12
4th rowMBARI/T488
5th rowAL-4097
ValueCountFrequency (%)
cb 3399
 
3.7%
moorea 3150
 
3.5%
fp 1215
 
1.3%
lrp 1032
 
1.1%
bah 989
 
1.1%
tob 834
 
0.9%
cur 810
 
0.9%
mbio/080611_minv_014 626
 
0.7%
dgs 506
 
0.6%
sec18-07 504
 
0.6%
Other values (7236) 78011
85.7%
2025-01-08T17:42:45.600552image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 78614
 
9.6%
- 70093
 
8.6%
1 62300
 
7.6%
B 45896
 
5.6%
2 43979
 
5.4%
I 35433
 
4.3%
M 34390
 
4.2%
A 34133
 
4.2%
3 27058
 
3.3%
8 21657
 
2.6%
Other values (63) 366049
44.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 325819
39.8%
Decimal Number 325257
39.7%
Dash Punctuation 70093
 
8.6%
Lowercase Letter 34318
 
4.2%
Other Punctuation 26173
 
3.2%
Space Separator 20135
 
2.5%
Connector Punctuation 17766
 
2.2%
Math Symbol 37
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
B 45896
14.1%
I 35433
10.9%
M 34390
10.6%
A 34133
10.5%
R 18890
 
5.8%
S 18631
 
5.7%
O 17074
 
5.2%
C 16693
 
5.1%
L 16123
 
4.9%
U 13273
 
4.1%
Other values (16) 75283
23.1%
Lowercase Letter
ValueCountFrequency (%)
o 7972
23.2%
e 4714
13.7%
r 3982
11.6%
a 3736
10.9%
n 2353
 
6.9%
i 1842
 
5.4%
m 1834
 
5.3%
t 1780
 
5.2%
v 1564
 
4.6%
l 1062
 
3.1%
Other values (15) 3479
10.1%
Decimal Number
ValueCountFrequency (%)
0 78614
24.2%
1 62300
19.2%
2 43979
13.5%
3 27058
 
8.3%
8 21657
 
6.7%
6 20171
 
6.2%
4 19688
 
6.1%
7 19207
 
5.9%
5 17520
 
5.4%
9 15063
 
4.6%
Other Punctuation
ValueCountFrequency (%)
/ 21508
82.2%
; 4624
 
17.7%
. 14
 
0.1%
# 14
 
0.1%
: 12
 
< 0.1%
, 1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 70093
100.0%
Space Separator
ValueCountFrequency (%)
20135
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 17766
100.0%
Math Symbol
ValueCountFrequency (%)
> 37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 459465
56.1%
Latin 360137
43.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
B 45896
12.7%
I 35433
 
9.8%
M 34390
 
9.5%
A 34133
 
9.5%
R 18890
 
5.2%
S 18631
 
5.2%
O 17074
 
4.7%
C 16693
 
4.6%
L 16123
 
4.5%
U 13273
 
3.7%
Other values (41) 109601
30.4%
Common
ValueCountFrequency (%)
0 78614
17.1%
- 70093
15.3%
1 62300
13.6%
2 43979
9.6%
3 27058
 
5.9%
8 21657
 
4.7%
/ 21508
 
4.7%
6 20171
 
4.4%
20135
 
4.4%
4 19688
 
4.3%
Other values (12) 74262
16.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 819601
> 99.9%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 78614
 
9.6%
- 70093
 
8.6%
1 62300
 
7.6%
B 45896
 
5.6%
2 43979
 
5.4%
I 35433
 
4.3%
M 34390
 
4.2%
A 34133
 
4.2%
3 27058
 
3.3%
8 21657
 
2.6%
Other values (62) 366048
44.7%
None
ValueCountFrequency (%)
é 1
100.0%

eventDate
Text

Missing 

Distinct23011
Distinct (%)7.2%
Missing16903
Missing (%)5.0%
Memory size2.6 MiB
2025-01-08T17:42:45.766092image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length10
Mean length11.0585446
Min length4

Characters and Unicode

Total characters3551905
Distinct characters17
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1361 ?
Unique (%)0.4%

Sample

1st row1977-05-21
2nd row2003-04-05
3rd row2009-12-05
4th row2006-09-14
5th row2003-05-01/2003-05-13
ValueCountFrequency (%)
2018-03-19/2018-03-23 1119
 
0.3%
2016-02-22/2016-03-09 840
 
0.3%
2008-06-11 649
 
0.2%
2017-05-26 623
 
0.2%
2015-05-09 524
 
0.2%
2017-05-23 518
 
0.2%
2017-05-30 515
 
0.2%
2006-03-12 513
 
0.2%
2017-08-14 508
 
0.2%
2017-05-27 505
 
0.2%
Other values (23001) 314877
98.0%
2025-01-08T17:42:45.990058image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 767941
21.6%
- 702212
19.8%
1 575030
16.2%
2 411303
11.6%
9 302111
 
8.5%
8 151019
 
4.3%
7 140049
 
3.9%
6 130946
 
3.7%
5 122995
 
3.5%
3 119921
 
3.4%
Other values (7) 128378
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2817587
79.3%
Dash Punctuation 702212
 
19.8%
Other Punctuation 32102
 
0.9%
Uppercase Letter 3
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 767941
27.3%
1 575030
20.4%
2 411303
14.6%
9 302111
 
10.7%
8 151019
 
5.4%
7 140049
 
5.0%
6 130946
 
4.6%
5 122995
 
4.4%
3 119921
 
4.3%
4 96272
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
P 1
33.3%
A 1
33.3%
N 1
33.3%
Other Punctuation
ValueCountFrequency (%)
/ 32100
> 99.9%
. 2
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 702212
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3551902
> 99.9%
Latin 3
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 767941
21.6%
- 702212
19.8%
1 575030
16.2%
2 411303
11.6%
9 302111
 
8.5%
8 151019
 
4.3%
7 140049
 
3.9%
6 130946
 
3.7%
5 122995
 
3.5%
3 119921
 
3.4%
Other values (4) 128375
 
3.6%
Latin
ValueCountFrequency (%)
P 1
33.3%
A 1
33.3%
N 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3551905
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 767941
21.6%
- 702212
19.8%
1 575030
16.2%
2 411303
11.6%
9 302111
 
8.5%
8 151019
 
4.3%
7 140049
 
3.9%
6 130946
 
3.7%
5 122995
 
3.5%
3 119921
 
3.4%
Other values (7) 128378
 
3.6%

eventTime
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing338093
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:46.043638image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowPinogana
ValueCountFrequency (%)
pinogana 1
100.0%
2025-01-08T17:42:46.131376image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 2
25.0%
a 2
25.0%
P 1
12.5%
i 1
12.5%
o 1
12.5%
g 1
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7
87.5%
Uppercase Letter 1
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 2
28.6%
a 2
28.6%
i 1
14.3%
o 1
14.3%
g 1
14.3%
Uppercase Letter
ValueCountFrequency (%)
P 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 2
25.0%
a 2
25.0%
P 1
12.5%
i 1
12.5%
o 1
12.5%
g 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 2
25.0%
a 2
25.0%
P 1
12.5%
i 1
12.5%
o 1
12.5%
g 1
12.5%

startDayOfYear
Text

Missing 

Distinct367
Distinct (%)0.1%
Missing19910
Missing (%)5.9%
Memory size2.6 MiB
2025-01-08T17:42:46.323821image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length11
Median length3
Mean length2.770698715
Min length1

Characters and Unicode

Total characters881592
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row141
2nd row95
3rd row339
4th row257
5th row121
ValueCountFrequency (%)
142 2410
 
0.8%
78 1961
 
0.6%
140 1910
 
0.6%
147 1848
 
0.6%
201 1848
 
0.6%
182 1823
 
0.6%
152 1822
 
0.6%
197 1811
 
0.6%
150 1809
 
0.6%
146 1797
 
0.6%
Other values (357) 299145
94.0%
2025-01-08T17:42:46.574206image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 192507
21.8%
2 156032
17.7%
3 99733
11.3%
4 66047
 
7.5%
5 65028
 
7.4%
7 63233
 
7.2%
6 60765
 
6.9%
0 60705
 
6.9%
8 59613
 
6.8%
9 57922
 
6.6%
Other values (5) 7
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 881585
> 99.9%
Other Punctuation 3
 
< 0.1%
Uppercase Letter 3
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 192507
21.8%
2 156032
17.7%
3 99733
11.3%
4 66047
 
7.5%
5 65028
 
7.4%
7 63233
 
7.2%
6 60765
 
6.9%
0 60705
 
6.9%
8 59613
 
6.8%
9 57922
 
6.6%
Uppercase Letter
ValueCountFrequency (%)
P 1
33.3%
A 1
33.3%
N 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 881589
> 99.9%
Latin 3
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 192507
21.8%
2 156032
17.7%
3 99733
11.3%
4 66047
 
7.5%
5 65028
 
7.4%
7 63233
 
7.2%
6 60765
 
6.9%
0 60705
 
6.9%
8 59613
 
6.8%
9 57922
 
6.6%
Other values (2) 4
 
< 0.1%
Latin
ValueCountFrequency (%)
P 1
33.3%
A 1
33.3%
N 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 881592
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 192507
21.8%
2 156032
17.7%
3 99733
11.3%
4 66047
 
7.5%
5 65028
 
7.4%
7 63233
 
7.2%
6 60765
 
6.9%
0 60705
 
6.9%
8 59613
 
6.8%
9 57922
 
6.6%
Other values (5) 7
 
< 0.1%

endDayOfYear
Text

Missing 

Distinct367
Distinct (%)0.1%
Missing19910
Missing (%)5.9%
Memory size2.6 MiB
2025-01-08T17:42:46.767431image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length3
Mean length2.778879516
Min length1

Characters and Unicode

Total characters884195
Distinct characters21
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row141
2nd row95
3rd row339
4th row257
5th row133
ValueCountFrequency (%)
142 2344
 
0.7%
151 2030
 
0.6%
150 2012
 
0.6%
82 1896
 
0.6%
69 1863
 
0.6%
143 1854
 
0.6%
212 1815
 
0.6%
197 1800
 
0.6%
146 1790
 
0.6%
147 1756
 
0.6%
Other values (359) 299026
94.0%
2025-01-08T17:42:47.013391image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 188897
21.4%
2 158630
17.9%
3 100399
11.4%
4 66204
 
7.5%
5 64939
 
7.3%
0 62735
 
7.1%
6 61927
 
7.0%
7 61685
 
7.0%
8 59642
 
6.7%
9 59125
 
6.7%
Other values (11) 12
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 884183
> 99.9%
Lowercase Letter 8
 
< 0.1%
Space Separator 2
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 188897
21.4%
2 158630
17.9%
3 100399
11.4%
4 66204
 
7.5%
5 64939
 
7.3%
0 62735
 
7.1%
6 61927
 
7.0%
7 61685
 
7.0%
8 59642
 
6.7%
9 59125
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
e 1
12.5%
p 1
12.5%
u 1
12.5%
d 1
12.5%
a 1
12.5%
c 1
12.5%
o 1
12.5%
é 1
12.5%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 884185
> 99.9%
Latin 10
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 188897
21.4%
2 158630
17.9%
3 100399
11.4%
4 66204
 
7.5%
5 64939
 
7.3%
0 62735
 
7.1%
6 61927
 
7.0%
7 61685
 
7.0%
8 59642
 
6.7%
9 59125
 
6.7%
Latin
ValueCountFrequency (%)
e 1
10.0%
p 1
10.0%
u 1
10.0%
C 1
10.0%
B 1
10.0%
d 1
10.0%
a 1
10.0%
c 1
10.0%
o 1
10.0%
é 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 884194
> 99.9%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 188897
21.4%
2 158630
17.9%
3 100399
11.4%
4 66204
 
7.5%
5 64939
 
7.3%
0 62735
 
7.1%
6 61927
 
7.0%
7 61685
 
7.0%
8 59642
 
6.7%
9 59125
 
6.7%
Other values (10) 11
 
< 0.1%
None
ValueCountFrequency (%)
é 1
100.0%

year
Text

Missing 

Distinct157
Distinct (%)< 0.1%
Missing17140
Missing (%)5.1%
Memory size2.6 MiB
2025-01-08T17:42:47.161659image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.999993769
Min length2

Characters and Unicode

Total characters1283814
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st row1977
2nd row2003
3rd row2009
4th row2006
5th row2003
ValueCountFrequency (%)
2009 14234
 
4.4%
2017 14047
 
4.4%
2015 13798
 
4.3%
2010 13719
 
4.3%
2012 12169
 
3.8%
2008 11965
 
3.7%
2016 11441
 
3.6%
2018 11080
 
3.5%
2019 9897
 
3.1%
2006 9359
 
2.9%
Other values (147) 199245
62.1%
2025-01-08T17:42:47.484244image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 294854
23.0%
1 274326
21.4%
2 222206
17.3%
9 214084
16.7%
8 70429
 
5.5%
7 60121
 
4.7%
6 50143
 
3.9%
5 37703
 
2.9%
3 30502
 
2.4%
4 29444
 
2.3%
Other values (2) 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1283812
> 99.9%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 294854
23.0%
1 274326
21.4%
2 222206
17.3%
9 214084
16.7%
8 70429
 
5.5%
7 60121
 
4.7%
6 50143
 
3.9%
5 37703
 
2.9%
3 30502
 
2.4%
4 29444
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
L 1
50.0%
C 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1283812
> 99.9%
Latin 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 294854
23.0%
1 274326
21.4%
2 222206
17.3%
9 214084
16.7%
8 70429
 
5.5%
7 60121
 
4.7%
6 50143
 
3.9%
5 37703
 
2.9%
3 30502
 
2.4%
4 29444
 
2.3%
Latin
ValueCountFrequency (%)
L 1
50.0%
C 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1283814
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 294854
23.0%
1 274326
21.4%
2 222206
17.3%
9 214084
16.7%
8 70429
 
5.5%
7 60121
 
4.7%
6 50143
 
3.9%
5 37703
 
2.9%
3 30502
 
2.4%
4 29444
 
2.3%
Other values (2) 2
 
< 0.1%

month
Text

Missing 

Distinct12
Distinct (%)< 0.1%
Missing22792
Missing (%)6.7%
Memory size2.6 MiB
2025-01-08T17:42:47.543702image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.179186938
Min length1

Characters and Unicode

Total characters371800
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row4
3rd row12
4th row9
5th row5
ValueCountFrequency (%)
5 42126
13.4%
6 36817
11.7%
7 36682
11.6%
8 30685
9.7%
4 28521
9.0%
3 27357
8.7%
9 25336
8.0%
10 23088
7.3%
11 20226
6.4%
2 15793
 
5.0%
Other values (2) 28671
9.1%
2025-01-08T17:42:47.644209image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 92211
24.8%
5 42126
11.3%
6 36817
 
9.9%
7 36682
 
9.9%
8 30685
 
8.3%
2 28977
 
7.8%
4 28521
 
7.7%
3 27357
 
7.4%
9 25336
 
6.8%
0 23088
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 371800
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 92211
24.8%
5 42126
11.3%
6 36817
 
9.9%
7 36682
 
9.9%
8 30685
 
8.3%
2 28977
 
7.8%
4 28521
 
7.7%
3 27357
 
7.4%
9 25336
 
6.8%
0 23088
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
Common 371800
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 92211
24.8%
5 42126
11.3%
6 36817
 
9.9%
7 36682
 
9.9%
8 30685
 
8.3%
2 28977
 
7.8%
4 28521
 
7.7%
3 27357
 
7.4%
9 25336
 
6.8%
0 23088
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 371800
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 92211
24.8%
5 42126
11.3%
6 36817
 
9.9%
7 36682
 
9.9%
8 30685
 
8.3%
2 28977
 
7.8%
4 28521
 
7.7%
3 27357
 
7.4%
9 25336
 
6.8%
0 23088
 
6.2%

day
Text

Missing 

Distinct32
Distinct (%)< 0.1%
Missing52010
Missing (%)15.4%
Memory size2.6 MiB
2025-01-08T17:42:47.722104image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length96
Median length2
Mean length1.706149243
Min length1

Characters and Unicode

Total characters488102
Distinct characters40
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row21
2nd row5
3rd row5
4th row14
5th row14
ValueCountFrequency (%)
16 10591
 
3.7%
11 10590
 
3.7%
8 10195
 
3.6%
10 10187
 
3.6%
5 10116
 
3.5%
15 10084
 
3.5%
12 10050
 
3.5%
14 9885
 
3.5%
7 9698
 
3.4%
22 9650
 
3.4%
Other values (35) 185051
64.7%
2025-01-08T17:42:47.852659image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 130494
26.7%
2 119138
24.4%
3 40129
 
8.2%
8 29336
 
6.0%
6 29314
 
6.0%
5 28584
 
5.9%
7 28048
 
5.7%
0 28006
 
5.7%
4 27568
 
5.6%
9 27393
 
5.6%
Other values (30) 92
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 488010
> 99.9%
Lowercase Letter 64
 
< 0.1%
Space Separator 13
 
< 0.1%
Uppercase Letter 9
 
< 0.1%
Other Punctuation 4
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 11
17.2%
o 7
10.9%
r 7
10.9%
a 5
7.8%
c 4
 
6.2%
i 4
 
6.2%
t 4
 
6.2%
n 4
 
6.2%
s 3
 
4.7%
d 3
 
4.7%
Other values (9) 12
18.8%
Decimal Number
ValueCountFrequency (%)
1 130494
26.7%
2 119138
24.4%
3 40129
 
8.2%
8 29336
 
6.0%
6 29314
 
6.0%
5 28584
 
5.9%
7 28048
 
5.7%
0 28006
 
5.7%
4 27568
 
5.6%
9 27393
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
G 3
33.3%
P 2
22.2%
B 1
 
11.1%
C 1
 
11.1%
W 1
 
11.1%
E 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
, 1
 
25.0%
Space Separator
ValueCountFrequency (%)
13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 488029
> 99.9%
Latin 73
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 11
15.1%
o 7
 
9.6%
r 7
 
9.6%
a 5
 
6.8%
c 4
 
5.5%
i 4
 
5.5%
t 4
 
5.5%
n 4
 
5.5%
s 3
 
4.1%
d 3
 
4.1%
Other values (15) 21
28.8%
Common
ValueCountFrequency (%)
1 130494
26.7%
2 119138
24.4%
3 40129
 
8.2%
8 29336
 
6.0%
6 29314
 
6.0%
5 28584
 
5.9%
7 28048
 
5.7%
0 28006
 
5.7%
4 27568
 
5.6%
9 27393
 
5.6%
Other values (5) 19
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 488102
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 130494
26.7%
2 119138
24.4%
3 40129
 
8.2%
8 29336
 
6.0%
6 29314
 
6.0%
5 28584
 
5.9%
7 28048
 
5.7%
0 28006
 
5.7%
4 27568
 
5.6%
9 27393
 
5.6%
Other values (30) 92
 
< 0.1%

verbatimEventDate
Text

Missing 

Distinct10231
Distinct (%)10.0%
Missing235843
Missing (%)69.8%
Memory size2.6 MiB
2025-01-08T17:42:48.026856image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length72
Median length71
Mean length13.69981712
Min length1

Characters and Unicode

Total characters1400820
Distinct characters76
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2669 ?
Unique (%)2.6%

Sample

1st row4/5/2003 3:59:00 PM
2nd row2007 or prior, based on filename of source data sheet
3rd row14 Sep 2006
4th row10/11/2002 1:30:00 PM
5th row11 May 2014
ValueCountFrequency (%)
may 10951
 
3.6%
apr 6716
 
2.2%
pm 6650
 
2.2%
aug 5881
 
1.9%
5371
 
1.8%
2007 5227
 
1.7%
sep 5183
 
1.7%
mar 4904
 
1.6%
2008 4654
 
1.5%
june 4026
 
1.3%
Other values (3776) 242866
80.3%
2025-01-08T17:42:48.285137image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
200178
 
14.3%
0 158992
 
11.3%
1 143302
 
10.2%
2 117701
 
8.4%
9 73185
 
5.2%
e 40939
 
2.9%
8 37291
 
2.7%
a 35798
 
2.6%
3 32860
 
2.3%
r 32280
 
2.3%
Other values (66) 528294
37.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 670885
47.9%
Lowercase Letter 313740
22.4%
Space Separator 200178
 
14.3%
Uppercase Letter 112844
 
8.1%
Other Punctuation 64360
 
4.6%
Dash Punctuation 30822
 
2.2%
Open Punctuation 3948
 
0.3%
Close Punctuation 3948
 
0.3%
Math Symbol 81
 
< 0.1%
Connector Punctuation 14
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 40939
13.0%
a 35798
11.4%
r 32280
10.3%
u 27456
8.8%
t 25372
 
8.1%
p 19853
 
6.3%
n 18252
 
5.8%
y 16737
 
5.3%
o 15204
 
4.8%
c 13230
 
4.2%
Other values (15) 68619
21.9%
Uppercase Letter
ValueCountFrequency (%)
M 25454
22.6%
J 20868
18.5%
A 19538
17.3%
S 12302
10.9%
N 7617
 
6.8%
P 6955
 
6.2%
D 5024
 
4.5%
O 4895
 
4.3%
F 4343
 
3.8%
E 1480
 
1.3%
Other values (11) 4368
 
3.9%
Other Punctuation
ValueCountFrequency (%)
: 32208
50.0%
/ 13150
20.4%
. 8664
 
13.5%
; 8151
 
12.7%
, 2129
 
3.3%
? 16
 
< 0.1%
* 15
 
< 0.1%
' 9
 
< 0.1%
& 6
 
< 0.1%
# 6
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
0 158992
23.7%
1 143302
21.4%
2 117701
17.5%
9 73185
10.9%
8 37291
 
5.6%
3 32860
 
4.9%
5 31291
 
4.7%
7 28000
 
4.2%
4 24299
 
3.6%
6 23964
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 30541
99.1%
281
 
0.9%
Open Punctuation
ValueCountFrequency (%)
[ 3930
99.5%
( 18
 
0.5%
Close Punctuation
ValueCountFrequency (%)
] 3930
99.5%
) 18
 
0.5%
Space Separator
ValueCountFrequency (%)
200178
100.0%
Math Symbol
ValueCountFrequency (%)
| 81
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 974236
69.5%
Latin 426584
30.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 40939
 
9.6%
a 35798
 
8.4%
r 32280
 
7.6%
u 27456
 
6.4%
M 25454
 
6.0%
t 25372
 
5.9%
J 20868
 
4.9%
p 19853
 
4.7%
A 19538
 
4.6%
n 18252
 
4.3%
Other values (36) 160774
37.7%
Common
ValueCountFrequency (%)
200178
20.5%
0 158992
16.3%
1 143302
14.7%
2 117701
12.1%
9 73185
 
7.5%
8 37291
 
3.8%
3 32860
 
3.4%
: 32208
 
3.3%
5 31291
 
3.2%
- 30541
 
3.1%
Other values (20) 116687
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1400539
> 99.9%
Punctuation 281
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
200178
 
14.3%
0 158992
 
11.4%
1 143302
 
10.2%
2 117701
 
8.4%
9 73185
 
5.2%
e 40939
 
2.9%
8 37291
 
2.7%
a 35798
 
2.6%
3 32860
 
2.3%
r 32280
 
2.3%
Other values (65) 528013
37.7%
Punctuation
ValueCountFrequency (%)
281
100.0%

habitat
Text

Missing 

Distinct5074
Distinct (%)14.1%
Missing302025
Missing (%)89.3%
Memory size2.6 MiB
2025-01-08T17:42:48.469297image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length382
Median length180
Mean length39.97022374
Min length1

Characters and Unicode

Total characters1441686
Distinct characters87
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1915 ?
Unique (%)5.3%

Sample

1st rowRocky slope with scattered shrubs. Moist soil on slope
2nd rowScrubland
3rd rowEcological remarks by collector(s): yes
4th rowCultivated/garden
5th rowbrushed from under rubble
ValueCountFrequency (%)
forest 9232
 
4.6%
and 8075
 
4.0%
with 6431
 
3.2%
by 4851
 
2.4%
ecological 4348
 
2.2%
remarks 4348
 
2.2%
collector(s 4343
 
2.2%
in 4299
 
2.1%
yes 3549
 
1.8%
slopes 2419
 
1.2%
Other values (4257) 150032
74.3%
2025-01-08T17:42:48.737688image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
165858
 
11.5%
e 122882
 
8.5%
a 115017
 
8.0%
r 97779
 
6.8%
o 97024
 
6.7%
s 87680
 
6.1%
i 77128
 
5.3%
n 73943
 
5.1%
t 69140
 
4.8%
l 65307
 
4.5%
Other values (77) 469928
32.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1158484
80.4%
Space Separator 165858
 
11.5%
Uppercase Letter 57641
 
4.0%
Other Punctuation 43972
 
3.1%
Open Punctuation 5085
 
0.4%
Close Punctuation 5081
 
0.4%
Decimal Number 3126
 
0.2%
Dash Punctuation 2287
 
0.2%
Math Symbol 151
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 122882
10.6%
a 115017
 
9.9%
r 97779
 
8.4%
o 97024
 
8.4%
s 87680
 
7.6%
i 77128
 
6.7%
n 73943
 
6.4%
t 69140
 
6.0%
l 65307
 
5.6%
c 52978
 
4.6%
Other values (17) 299606
25.9%
Uppercase Letter
ValueCountFrequency (%)
E 6024
 
10.5%
C 5575
 
9.7%
S 5336
 
9.3%
A 5260
 
9.1%
P 4281
 
7.4%
M 4222
 
7.3%
R 4146
 
7.2%
B 3101
 
5.4%
D 2366
 
4.1%
G 2064
 
3.6%
Other values (16) 15266
26.5%
Other Punctuation
ValueCountFrequency (%)
, 22792
51.8%
. 11645
26.5%
: 4679
 
10.6%
/ 2864
 
6.5%
; 1481
 
3.4%
& 181
 
0.4%
% 121
 
0.3%
" 101
 
0.2%
? 72
 
0.2%
' 24
 
0.1%
Other values (2) 12
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
0 714
22.8%
1 509
16.3%
2 394
12.6%
5 351
11.2%
3 258
 
8.3%
8 219
 
7.0%
4 196
 
6.3%
6 173
 
5.5%
7 162
 
5.2%
9 150
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 2275
99.5%
8
 
0.3%
4
 
0.2%
Math Symbol
ValueCountFrequency (%)
~ 138
91.4%
+ 8
 
5.3%
< 5
 
3.3%
Open Punctuation
ValueCountFrequency (%)
( 5049
99.3%
[ 36
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 5045
99.3%
] 36
 
0.7%
Space Separator
ValueCountFrequency (%)
165858
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1216125
84.4%
Common 225561
 
15.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 122882
 
10.1%
a 115017
 
9.5%
r 97779
 
8.0%
o 97024
 
8.0%
s 87680
 
7.2%
i 77128
 
6.3%
n 73943
 
6.1%
t 69140
 
5.7%
l 65307
 
5.4%
c 52978
 
4.4%
Other values (43) 357247
29.4%
Common
ValueCountFrequency (%)
165858
73.5%
, 22792
 
10.1%
. 11645
 
5.2%
( 5049
 
2.2%
) 5045
 
2.2%
: 4679
 
2.1%
/ 2864
 
1.3%
- 2275
 
1.0%
; 1481
 
0.7%
0 714
 
0.3%
Other values (24) 3159
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1441668
> 99.9%
Punctuation 12
 
< 0.1%
None 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
165858
 
11.5%
e 122882
 
8.5%
a 115017
 
8.0%
r 97779
 
6.8%
o 97024
 
6.7%
s 87680
 
6.1%
i 77128
 
5.3%
n 73943
 
5.1%
t 69140
 
4.8%
l 65307
 
4.5%
Other values (74) 469910
32.6%
Punctuation
ValueCountFrequency (%)
8
66.7%
4
33.3%
None
ValueCountFrequency (%)
ñ 6
100.0%

locationID
Text

Missing 

Distinct4570
Distinct (%)8.5%
Missing284620
Missing (%)84.2%
Memory size2.6 MiB
2025-01-08T17:42:48.919466image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length28
Mean length6.812862326
Min length1

Characters and Unicode

Total characters364311
Distinct characters83
Distinct categories12 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1199 ?
Unique (%)2.2%

Sample

1st rowT548
2nd rowBIZ-231
3rd rowT488
4th row02-10
5th rowVES117
ValueCountFrequency (%)
080611_minv_014 627
 
1.1%
site 469
 
0.8%
trawl 456
 
0.8%
i 456
 
0.8%
serc 326
 
0.6%
14 313
 
0.6%
v1951 308
 
0.5%
080608_minv_012 289
 
0.5%
10 275
 
0.5%
21 275
 
0.5%
Other values (4452) 53036
93.3%
2025-01-08T17:42:49.163399image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 37140
 
10.2%
1 34688
 
9.5%
- 19187
 
5.3%
2 18285
 
5.0%
I 15952
 
4.4%
_ 15373
 
4.2%
5 13776
 
3.8%
4 13693
 
3.8%
8 13263
 
3.6%
6 12669
 
3.5%
Other values (73) 170285
46.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 176505
48.4%
Uppercase Letter 123781
34.0%
Lowercase Letter 23388
 
6.4%
Dash Punctuation 19187
 
5.3%
Connector Punctuation 15373
 
4.2%
Space Separator 3356
 
0.9%
Other Punctuation 2271
 
0.6%
Open Punctuation 203
 
0.1%
Close Punctuation 202
 
0.1%
Math Symbol 40
 
< 0.1%
Other values (2) 5
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
I 15952
12.9%
A 12413
 
10.0%
B 12220
 
9.9%
S 9794
 
7.9%
M 9584
 
7.7%
T 7525
 
6.1%
Z 6269
 
5.1%
O 5814
 
4.7%
N 5745
 
4.6%
V 4402
 
3.6%
Other values (18) 34063
27.5%
Lowercase Letter
ValueCountFrequency (%)
n 2390
10.2%
i 2331
10.0%
e 1964
 
8.4%
m 1947
 
8.3%
o 1868
 
8.0%
a 1852
 
7.9%
t 1743
 
7.5%
r 1556
 
6.7%
v 1293
 
5.5%
g 941
 
4.0%
Other values (17) 5503
23.5%
Decimal Number
ValueCountFrequency (%)
0 37140
21.0%
1 34688
19.7%
2 18285
10.4%
5 13776
 
7.8%
4 13693
 
7.8%
8 13263
 
7.5%
6 12669
 
7.2%
3 12421
 
7.0%
7 11375
 
6.4%
9 9195
 
5.2%
Other Punctuation
ValueCountFrequency (%)
/ 1117
49.2%
. 1044
46.0%
# 108
 
4.8%
, 2
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 196
96.6%
[ 6
 
3.0%
1
 
0.5%
Math Symbol
ValueCountFrequency (%)
> 37
92.5%
¬ 2
 
5.0%
+ 1
 
2.5%
Close Punctuation
ValueCountFrequency (%)
) 196
97.0%
] 6
 
3.0%
Currency Symbol
ValueCountFrequency (%)
¢ 3
75.0%
1
 
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 19187
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 15373
100.0%
Space Separator
ValueCountFrequency (%)
3356
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 217142
59.6%
Latin 147169
40.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
I 15952
 
10.8%
A 12413
 
8.4%
B 12220
 
8.3%
S 9794
 
6.7%
M 9584
 
6.5%
T 7525
 
5.1%
Z 6269
 
4.3%
O 5814
 
4.0%
N 5745
 
3.9%
V 4402
 
3.0%
Other values (45) 57451
39.0%
Common
ValueCountFrequency (%)
0 37140
17.1%
1 34688
16.0%
- 19187
8.8%
2 18285
8.4%
_ 15373
7.1%
5 13776
 
6.3%
4 13693
 
6.3%
8 13263
 
6.1%
6 12669
 
5.8%
3 12421
 
5.7%
Other values (18) 26647
12.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 364293
> 99.9%
None 15
 
< 0.1%
Punctuation 2
 
< 0.1%
Currency Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 37140
 
10.2%
1 34688
 
9.5%
- 19187
 
5.3%
2 18285
 
5.0%
I 15952
 
4.4%
_ 15373
 
4.2%
5 13776
 
3.8%
4 13693
 
3.8%
8 13263
 
3.6%
6 12669
 
3.5%
Other values (62) 170267
46.7%
None
ValueCountFrequency (%)
à 3
20.0%
¢ 3
20.0%
 2
13.3%
â 2
13.3%
¬ 2
13.3%
ƒ 1
 
6.7%
š 1
 
6.7%
Å 1
 
6.7%
Currency Symbols
ValueCountFrequency (%)
1
100.0%
Punctuation
ValueCountFrequency (%)
1
50.0%
1
50.0%

higherGeography
Text

Missing 

Distinct7779
Distinct (%)2.3%
Missing4531
Missing (%)1.3%
Memory size2.6 MiB
2025-01-08T17:42:49.350980image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length128
Median length103
Mean length44.48305717
Min length4

Characters and Unicode

Total characters14837902
Distinct characters98
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique787 ?
Unique (%)0.2%

Sample

1st rowUnited States, Arizona, Cochise
2nd rowNorth Pacific Ocean, Gulf of California, Mexico
3rd rowSouth Pacific Ocean, French Polynesia, Society Islands, Moorea
4th rowUnited States, Arkansas
5th rowAsia-Temperate, China, Xizang, Nielamu (Nyalam) Xian
ValueCountFrequency (%)
states 150734
 
7.6%
united 150654
 
7.6%
north 101817
 
5.1%
ocean 69413
 
3.5%
pacific 66261
 
3.4%
america 65435
 
3.3%
not 60307
 
3.0%
stated 60307
 
3.0%
islands 44071
 
2.2%
atlantic 41374
 
2.1%
Other values (4525) 1167157
59.0%
2025-01-08T17:42:49.613764image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1643967
 
11.1%
a 1472182
 
9.9%
t 1108058
 
7.5%
e 1084394
 
7.3%
i 1040753
 
7.0%
n 860928
 
5.8%
, 825692
 
5.6%
o 731207
 
4.9%
r 620008
 
4.2%
s 541802
 
3.7%
Other values (88) 4908911
33.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10246955
69.1%
Uppercase Letter 1952392
 
13.2%
Space Separator 1643967
 
11.1%
Other Punctuation 836703
 
5.6%
Close Punctuation 63011
 
0.4%
Open Punctuation 63011
 
0.4%
Dash Punctuation 30878
 
0.2%
Modifier Letter 813
 
< 0.1%
Decimal Number 169
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 1472182
14.4%
t 1108058
10.8%
e 1084394
10.6%
i 1040753
10.2%
n 860928
8.4%
o 731207
 
7.1%
r 620008
 
6.1%
s 541802
 
5.3%
c 500877
 
4.9%
l 396581
 
3.9%
Other values (36) 1890165
18.4%
Uppercase Letter
ValueCountFrequency (%)
S 344369
17.6%
N 206279
10.6%
A 200821
10.3%
C 181308
9.3%
U 160228
8.2%
P 159029
8.1%
M 93185
 
4.8%
O 87914
 
4.5%
B 72819
 
3.7%
I 68288
 
3.5%
Other values (20) 378152
19.4%
Other Punctuation
ValueCountFrequency (%)
, 825692
98.7%
. 7803
 
0.9%
' 2811
 
0.3%
? 201
 
< 0.1%
/ 190
 
< 0.1%
* 5
 
< 0.1%
; 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
3 108
63.9%
1 24
 
14.2%
2 16
 
9.5%
9 13
 
7.7%
0 8
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 30862
99.9%
10
 
< 0.1%
6
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
] 61090
97.0%
) 1921
 
3.0%
Open Punctuation
ValueCountFrequency (%)
[ 61090
97.0%
( 1921
 
3.0%
Space Separator
ValueCountFrequency (%)
1643967
100.0%
Modifier Letter
ValueCountFrequency (%)
ʻ 813
100.0%
Math Symbol
ValueCountFrequency (%)
= 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12199347
82.2%
Common 2638555
 
17.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 1472182
 
12.1%
t 1108058
 
9.1%
e 1084394
 
8.9%
i 1040753
 
8.5%
n 860928
 
7.1%
o 731207
 
6.0%
r 620008
 
5.1%
s 541802
 
4.4%
c 500877
 
4.1%
l 396581
 
3.3%
Other values (66) 3842557
31.5%
Common
ValueCountFrequency (%)
1643967
62.3%
, 825692
31.3%
] 61090
 
2.3%
[ 61090
 
2.3%
- 30862
 
1.2%
. 7803
 
0.3%
' 2811
 
0.1%
) 1921
 
0.1%
( 1921
 
0.1%
ʻ 813
 
< 0.1%
Other values (12) 585
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14824256
99.9%
None 12817
 
0.1%
Modifier Letters 813
 
< 0.1%
Punctuation 16
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1643967
 
11.1%
a 1472182
 
9.9%
t 1108058
 
7.5%
e 1084394
 
7.3%
i 1040753
 
7.0%
n 860928
 
5.8%
, 825692
 
5.6%
o 731207
 
4.9%
r 620008
 
4.2%
s 541802
 
3.7%
Other values (61) 4895265
33.0%
None
ValueCountFrequency (%)
é 3472
27.1%
í 2109
16.5%
ã 1904
14.9%
Î 1377
 
10.7%
ó 1025
 
8.0%
ā 813
 
6.3%
ç 805
 
6.3%
á 431
 
3.4%
ä 239
 
1.9%
ö 194
 
1.5%
Other values (14) 448
 
3.5%
Modifier Letters
ValueCountFrequency (%)
ʻ 813
100.0%
Punctuation
ValueCountFrequency (%)
10
62.5%
6
37.5%

continent
Text

Missing 

Distinct7
Distinct (%)< 0.1%
Missing57738
Missing (%)17.1%
Memory size2.6 MiB
2025-01-08T17:42:49.673691image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length10.55335716
Min length4

Characters and Unicode

Total characters2958697
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNORTH_AMERICA
2nd rowOCEANIA
3rd rowASIA
4th rowAFRICA
5th rowOCEANIA
ValueCountFrequency (%)
north_america 154617
55.2%
oceania 41626
 
14.8%
asia 32094
 
11.4%
south_america 30956
 
11.0%
africa 17455
 
6.2%
europe 3580
 
1.3%
antarctica 28
 
< 0.1%
2025-01-08T17:42:49.775177image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 553580
18.7%
R 361253
12.2%
I 276776
9.4%
C 244710
8.3%
E 234359
7.9%
O 230779
7.8%
N 196271
 
6.6%
T 185629
 
6.3%
H 185573
 
6.3%
_ 185573
 
6.3%
Other values (5) 304194
10.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2773124
93.7%
Connector Punctuation 185573
 
6.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 553580
20.0%
R 361253
13.0%
I 276776
10.0%
C 244710
8.8%
E 234359
8.5%
O 230779
8.3%
N 196271
 
7.1%
T 185629
 
6.7%
H 185573
 
6.7%
M 185573
 
6.7%
Other values (4) 118621
 
4.3%
Connector Punctuation
ValueCountFrequency (%)
_ 185573
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2773124
93.7%
Common 185573
 
6.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 553580
20.0%
R 361253
13.0%
I 276776
10.0%
C 244710
8.8%
E 234359
8.5%
O 230779
8.3%
N 196271
 
7.1%
T 185629
 
6.7%
H 185573
 
6.7%
M 185573
 
6.7%
Other values (4) 118621
 
4.3%
Common
ValueCountFrequency (%)
_ 185573
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2958697
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 553580
18.7%
R 361253
12.2%
I 276776
9.4%
C 244710
8.3%
E 234359
7.9%
O 230779
7.8%
N 196271
 
6.6%
T 185629
 
6.3%
H 185573
 
6.3%
_ 185573
 
6.3%
Other values (5) 304194
10.3%

waterBody
Text

Missing 

Distinct217
Distinct (%)0.2%
Missing231346
Missing (%)68.4%
Memory size2.6 MiB
2025-01-08T17:42:49.915442image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length69
Median length53
Mean length20.41937085
Min length6

Characters and Unicode

Total characters2179727
Distinct characters55
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)< 0.1%

Sample

1st rowNorth Pacific Ocean, Gulf of California
2nd rowSouth Pacific Ocean
3rd rowNorth Atlantic Ocean
4th rowPacific
5th rowNorth Pacific Ocean
ValueCountFrequency (%)
ocean 69162
21.1%
pacific 61578
18.8%
north 47089
14.4%
atlantic 41318
12.6%
south 18400
 
5.6%
sea 18234
 
5.6%
caribbean 14724
 
4.5%
bay 12118
 
3.7%
gulf 7267
 
2.2%
of 6749
 
2.1%
Other values (198) 31204
9.5%
2025-01-08T17:42:50.133492image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 263495
12.1%
c 237624
10.9%
221095
 
10.1%
i 195151
 
9.0%
t 152988
 
7.0%
n 144138
 
6.6%
e 133315
 
6.1%
o 87930
 
4.0%
f 78762
 
3.6%
h 75874
 
3.5%
Other values (45) 589355
27.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1598402
73.3%
Uppercase Letter 321268
 
14.7%
Space Separator 221095
 
10.1%
Other Punctuation 38149
 
1.8%
Modifier Letter 813
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 263495
16.5%
c 237624
14.9%
i 195151
12.2%
t 152988
9.6%
n 144138
9.0%
e 133315
8.3%
o 87930
 
5.5%
f 78762
 
4.9%
h 75874
 
4.7%
r 70327
 
4.4%
Other values (16) 158798
9.9%
Uppercase Letter
ValueCountFrequency (%)
O 69662
21.7%
P 64644
20.1%
N 47095
14.7%
A 41986
13.1%
S 38909
12.1%
C 22284
 
6.9%
B 14232
 
4.4%
G 7323
 
2.3%
K 4833
 
1.5%
M 3987
 
1.2%
Other values (13) 6313
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 38070
99.8%
' 73
 
0.2%
. 5
 
< 0.1%
; 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
221095
100.0%
Modifier Letter
ValueCountFrequency (%)
ʻ 813
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1919670
88.1%
Common 260057
 
11.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 263495
13.7%
c 237624
12.4%
i 195151
10.2%
t 152988
 
8.0%
n 144138
 
7.5%
e 133315
 
6.9%
o 87930
 
4.6%
f 78762
 
4.1%
h 75874
 
4.0%
r 70327
 
3.7%
Other values (39) 480066
25.0%
Common
ValueCountFrequency (%)
221095
85.0%
, 38070
 
14.6%
ʻ 813
 
0.3%
' 73
 
< 0.1%
. 5
 
< 0.1%
; 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2178101
99.9%
None 813
 
< 0.1%
Modifier Letters 813
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 263495
12.1%
c 237624
10.9%
221095
 
10.2%
i 195151
 
9.0%
t 152988
 
7.0%
n 144138
 
6.6%
e 133315
 
6.1%
o 87930
 
4.0%
f 78762
 
3.6%
h 75874
 
3.5%
Other values (43) 587729
27.0%
None
ValueCountFrequency (%)
ā 813
100.0%
Modifier Letters
ValueCountFrequency (%)
ʻ 813
100.0%

islandGroup
Text

Missing 

Distinct100
Distinct (%)0.4%
Missing315374
Missing (%)93.3%
Memory size2.6 MiB
2025-01-08T17:42:50.239681image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length21
Mean length14.50514965
Min length5

Characters and Unicode

Total characters329557
Distinct characters51
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)< 0.1%

Sample

1st rowSociety Islands
2nd rowLeeward Antilles
3rd rowBahama Islands
4th rowSociety Islands
5th rowVisayas
ValueCountFrequency (%)
islands 15107
31.9%
society 10375
21.9%
leeward 3580
 
7.6%
antilles 3191
 
6.7%
îles 1360
 
2.9%
vent 1360
 
2.9%
du 1300
 
2.7%
cays 1105
 
2.3%
bahama 989
 
2.1%
group 827
 
1.7%
Other values (103) 8209
17.3%
2025-01-08T17:42:50.409854image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 39205
11.9%
a 28802
 
8.7%
e 28031
 
8.5%
24683
 
7.5%
l 24467
 
7.4%
n 22700
 
6.9%
d 21934
 
6.7%
i 17625
 
5.3%
t 16043
 
4.9%
I 15495
 
4.7%
Other values (41) 90572
27.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 256862
77.9%
Uppercase Letter 47651
 
14.5%
Space Separator 24683
 
7.5%
Other Punctuation 361
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 39205
15.3%
a 28802
11.2%
e 28031
10.9%
l 24467
9.5%
n 22700
8.8%
d 21934
8.5%
i 17625
6.9%
t 16043
6.2%
o 12680
 
4.9%
y 11936
 
4.6%
Other values (15) 33439
13.0%
Uppercase Letter
ValueCountFrequency (%)
I 15495
32.5%
S 11283
23.7%
L 4421
 
9.3%
A 4266
 
9.0%
V 2159
 
4.5%
B 2058
 
4.3%
C 2045
 
4.3%
Î 1360
 
2.9%
P 926
 
1.9%
G 916
 
1.9%
Other values (13) 2722
 
5.7%
Other Punctuation
ValueCountFrequency (%)
. 353
97.8%
' 8
 
2.2%
Space Separator
ValueCountFrequency (%)
24683
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 304513
92.4%
Common 25044
 
7.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 39205
12.9%
a 28802
 
9.5%
e 28031
 
9.2%
l 24467
 
8.0%
n 22700
 
7.5%
d 21934
 
7.2%
i 17625
 
5.8%
t 16043
 
5.3%
I 15495
 
5.1%
o 12680
 
4.2%
Other values (38) 77531
25.5%
Common
ValueCountFrequency (%)
24683
98.6%
. 353
 
1.4%
' 8
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 328197
99.6%
None 1360
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 39205
11.9%
a 28802
 
8.8%
e 28031
 
8.5%
24683
 
7.5%
l 24467
 
7.5%
n 22700
 
6.9%
d 21934
 
6.7%
i 17625
 
5.4%
t 16043
 
4.9%
I 15495
 
4.7%
Other values (40) 89212
27.2%
None
ValueCountFrequency (%)
Î 1360
100.0%

island
Text

Missing 

Distinct566
Distinct (%)1.0%
Missing279260
Missing (%)82.6%
Memory size2.6 MiB
2025-01-08T17:42:50.592323image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length31
Median length25
Mean length8.431383214
Min length3

Characters and Unicode

Total characters496052
Distinct characters62
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)0.1%

Sample

1st rowMoorea
2nd rowMoorea
3rd rowMindanao
4th rowKlein Curacao
5th rowMoorea
ValueCountFrequency (%)
moorea 15941
18.5%
cay 7341
 
8.5%
carrie 4785
 
5.5%
bow 4785
 
5.5%
island 4062
 
4.7%
curacao 3674
 
4.3%
oahu 2249
 
2.6%
luzon 2088
 
2.4%
borneo 2043
 
2.4%
atoll 914
 
1.1%
Other values (560) 38461
44.5%
2025-01-08T17:42:50.833124image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 78531
15.8%
o 63637
12.8%
r 44894
 
9.1%
e 38281
 
7.7%
27509
 
5.5%
u 21061
 
4.2%
n 20954
 
4.2%
i 20832
 
4.2%
C 19923
 
4.0%
M 19688
 
4.0%
Other values (52) 140742
28.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 379929
76.6%
Uppercase Letter 86074
 
17.4%
Space Separator 27509
 
5.5%
Close Punctuation 801
 
0.2%
Open Punctuation 801
 
0.2%
Other Punctuation 780
 
0.2%
Dash Punctuation 158
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 78531
20.7%
o 63637
16.7%
r 44894
11.8%
e 38281
10.1%
u 21061
 
5.5%
n 20954
 
5.5%
i 20832
 
5.5%
l 12002
 
3.2%
s 11378
 
3.0%
y 10662
 
2.8%
Other values (19) 57697
15.2%
Uppercase Letter
ValueCountFrequency (%)
C 19923
23.1%
M 19688
22.9%
B 8928
10.4%
I 4675
 
5.4%
T 4460
 
5.2%
S 3543
 
4.1%
L 3257
 
3.8%
H 2574
 
3.0%
O 2570
 
3.0%
P 2469
 
2.9%
Other values (16) 13987
16.2%
Other Punctuation
ValueCountFrequency (%)
' 705
90.4%
. 73
 
9.4%
, 2
 
0.3%
Space Separator
ValueCountFrequency (%)
27509
100.0%
Close Punctuation
ValueCountFrequency (%)
] 801
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 801
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 158
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 466003
93.9%
Common 30049
 
6.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 78531
16.9%
o 63637
13.7%
r 44894
 
9.6%
e 38281
 
8.2%
u 21061
 
4.5%
n 20954
 
4.5%
i 20832
 
4.5%
C 19923
 
4.3%
M 19688
 
4.2%
l 12002
 
2.6%
Other values (45) 126200
27.1%
Common
ValueCountFrequency (%)
27509
91.5%
] 801
 
2.7%
[ 801
 
2.7%
' 705
 
2.3%
- 158
 
0.5%
. 73
 
0.2%
, 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 495602
99.9%
None 450
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 78531
15.8%
o 63637
12.8%
r 44894
 
9.1%
e 38281
 
7.7%
27509
 
5.6%
u 21061
 
4.2%
n 20954
 
4.2%
i 20832
 
4.2%
C 19923
 
4.0%
M 19688
 
4.0%
Other values (47) 140292
28.3%
None
ValueCountFrequency (%)
ç 380
84.4%
ó 34
 
7.6%
ò 19
 
4.2%
Î 14
 
3.1%
Ž 3
 
0.7%

countryCode
Text

Missing 

Distinct203
Distinct (%)0.1%
Missing11127
Missing (%)3.3%
Memory size2.6 MiB
2025-01-08T17:42:50.995853image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters653934
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st rowUS
2nd rowMX
3rd rowPF
4th rowUS
5th rowCN
ValueCountFrequency (%)
us 150956
46.2%
pf 22993
 
7.0%
mx 10948
 
3.3%
pa 9204
 
2.8%
bz 9189
 
2.8%
mm 8052
 
2.5%
ph 6777
 
2.1%
gy 5990
 
1.8%
pg 4467
 
1.4%
cw 4291
 
1.3%
Other values (193) 94100
28.8%
2025-01-08T17:42:51.199671image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 158858
24.3%
U 156371
23.9%
P 51767
 
7.9%
M 36656
 
5.6%
F 27494
 
4.2%
C 25318
 
3.9%
A 21589
 
3.3%
G 20634
 
3.2%
B 18213
 
2.8%
Z 16360
 
2.5%
Other values (16) 120674
18.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 653934
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 158858
24.3%
U 156371
23.9%
P 51767
 
7.9%
M 36656
 
5.6%
F 27494
 
4.2%
C 25318
 
3.9%
A 21589
 
3.3%
G 20634
 
3.2%
B 18213
 
2.8%
Z 16360
 
2.5%
Other values (16) 120674
18.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 653934
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 158858
24.3%
U 156371
23.9%
P 51767
 
7.9%
M 36656
 
5.6%
F 27494
 
4.2%
C 25318
 
3.9%
A 21589
 
3.3%
G 20634
 
3.2%
B 18213
 
2.8%
Z 16360
 
2.5%
Other values (16) 120674
18.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 653934
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 158858
24.3%
U 156371
23.9%
P 51767
 
7.9%
M 36656
 
5.6%
F 27494
 
4.2%
C 25318
 
3.9%
A 21589
 
3.3%
G 20634
 
3.2%
B 18213
 
2.8%
Z 16360
 
2.5%
Other values (16) 120674
18.5%

stateProvince
Text

Missing 

Distinct1646
Distinct (%)0.6%
Missing66137
Missing (%)19.6%
Memory size2.6 MiB
2025-01-08T17:42:51.381428image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length52
Median length42
Mean length9.616295959
Min length3

Characters and Unicode

Total characters2615219
Distinct characters82
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)< 0.1%

Sample

1st rowArizona
2nd rowArkansas
3rd rowXizang
4th rowLaikipia
5th rowFlorida
ValueCountFrequency (%)
california 17057
 
4.6%
florida 16471
 
4.4%
texas 14319
 
3.9%
virginia 13034
 
3.5%
not 10630
 
2.9%
stated 10630
 
2.9%
arizona 9677
 
2.6%
carolina 8845
 
2.4%
region 8363
 
2.3%
new 8067
 
2.2%
Other values (1667) 253487
68.4%
2025-01-08T17:42:51.639387image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 361404
13.8%
i 256979
 
9.8%
n 192389
 
7.4%
o 190990
 
7.3%
r 175132
 
6.7%
e 143513
 
5.5%
s 116807
 
4.5%
t 109006
 
4.2%
l 104505
 
4.0%
98623
 
3.8%
Other values (72) 865871
33.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2112662
80.8%
Uppercase Letter 370786
 
14.2%
Space Separator 98623
 
3.8%
Open Punctuation 10906
 
0.4%
Close Punctuation 10906
 
0.4%
Dash Punctuation 8610
 
0.3%
Other Punctuation 2605
 
0.1%
Decimal Number 121
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 361404
17.1%
i 256979
12.2%
n 192389
9.1%
o 190990
9.0%
r 175132
8.3%
e 143513
 
6.8%
s 116807
 
5.5%
t 109006
 
5.2%
l 104505
 
4.9%
u 68862
 
3.3%
Other values (31) 393075
18.6%
Uppercase Letter
ValueCountFrequency (%)
C 47905
12.9%
T 35455
 
9.6%
S 34249
 
9.2%
N 33647
 
9.1%
M 32034
 
8.6%
A 24596
 
6.6%
F 18709
 
5.0%
V 16282
 
4.4%
P 16173
 
4.4%
I 12002
 
3.2%
Other values (18) 99734
26.9%
Other Punctuation
ValueCountFrequency (%)
. 2197
84.3%
' 211
 
8.1%
/ 93
 
3.6%
, 61
 
2.3%
? 43
 
1.7%
Open Punctuation
ValueCountFrequency (%)
[ 10606
97.2%
( 300
 
2.8%
Close Punctuation
ValueCountFrequency (%)
] 10606
97.2%
) 300
 
2.8%
Decimal Number
ValueCountFrequency (%)
3 108
89.3%
9 13
 
10.7%
Space Separator
ValueCountFrequency (%)
98623
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8610
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2483448
95.0%
Common 131771
 
5.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 361404
14.6%
i 256979
 
10.3%
n 192389
 
7.7%
o 190990
 
7.7%
r 175132
 
7.1%
e 143513
 
5.8%
s 116807
 
4.7%
t 109006
 
4.4%
l 104505
 
4.2%
u 68862
 
2.8%
Other values (59) 763861
30.8%
Common
ValueCountFrequency (%)
98623
74.8%
[ 10606
 
8.0%
] 10606
 
8.0%
- 8610
 
6.5%
. 2197
 
1.7%
( 300
 
0.2%
) 300
 
0.2%
' 211
 
0.2%
3 108
 
0.1%
/ 93
 
0.1%
Other values (3) 117
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2608986
99.8%
None 6233
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 361404
13.9%
i 256979
 
9.8%
n 192389
 
7.4%
o 190990
 
7.3%
r 175132
 
6.7%
e 143513
 
5.5%
s 116807
 
4.5%
t 109006
 
4.2%
l 104505
 
4.0%
98623
 
3.8%
Other values (55) 859638
32.9%
None
ValueCountFrequency (%)
é 2424
38.9%
ã 977
15.7%
ó 950
 
15.2%
í 867
 
13.9%
á 390
 
6.3%
ä 239
 
3.8%
ö 185
 
3.0%
ñ 88
 
1.4%
ô 45
 
0.7%
ü 17
 
0.3%
Other values (7) 51
 
0.8%

county
Text

Missing 

Distinct3053
Distinct (%)1.5%
Missing140475
Missing (%)41.5%
Memory size2.6 MiB
2025-01-08T17:42:51.818262image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length56
Median length35
Mean length10.83467683
Min length1

Characters and Unicode

Total characters2141138
Distinct characters83
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique295 ?
Unique (%)0.1%

Sample

1st rowCochise
2nd rowNielamu (Nyalam) Xian
3rd row[Not Stated]
4th row[Not Stated]
5th row[Not Stated]
ValueCountFrequency (%)
not 49620
 
15.0%
stated 49620
 
15.0%
county 38478
 
11.6%
honolulu 5034
 
1.5%
san 4615
 
1.4%
st 3587
 
1.1%
cochise 3337
 
1.0%
lucie 3224
 
1.0%
island 2682
 
0.8%
xian 2350
 
0.7%
Other values (2542) 168921
51.0%
2025-01-08T17:42:52.057811image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 236676
 
11.1%
o 187861
 
8.8%
a 183049
 
8.5%
e 150027
 
7.0%
n 138728
 
6.5%
133849
 
6.3%
u 85231
 
4.0%
i 84530
 
3.9%
d 76606
 
3.6%
r 76271
 
3.6%
Other values (73) 788310
36.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1567038
73.2%
Uppercase Letter 329801
 
15.4%
Space Separator 133849
 
6.3%
Open Punctuation 50849
 
2.4%
Close Punctuation 50849
 
2.4%
Other Punctuation 6646
 
0.3%
Dash Punctuation 2055
 
0.1%
Decimal Number 48
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 236676
15.1%
o 187861
12.0%
a 183049
11.7%
e 150027
9.6%
n 138728
8.9%
u 85231
 
5.4%
i 84530
 
5.4%
d 76606
 
4.9%
r 76271
 
4.9%
l 60245
 
3.8%
Other values (28) 287814
18.4%
Uppercase Letter
ValueCountFrequency (%)
S 72930
22.1%
C 59829
18.1%
N 54898
16.6%
H 14147
 
4.3%
B 13868
 
4.2%
M 13860
 
4.2%
P 13308
 
4.0%
L 12983
 
3.9%
A 12161
 
3.7%
D 9867
 
3.0%
Other values (18) 51950
15.8%
Other Punctuation
ValueCountFrequency (%)
. 4070
61.2%
' 1743
26.2%
, 625
 
9.4%
? 107
 
1.6%
/ 96
 
1.4%
* 5
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 24
50.0%
2 16
33.3%
0 8
 
16.7%
Open Punctuation
ValueCountFrequency (%)
[ 49629
97.6%
( 1220
 
2.4%
Close Punctuation
ValueCountFrequency (%)
] 49629
97.6%
) 1220
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 2045
99.5%
10
 
0.5%
Space Separator
ValueCountFrequency (%)
133849
100.0%
Math Symbol
ValueCountFrequency (%)
= 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1896839
88.6%
Common 244299
 
11.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 236676
 
12.5%
o 187861
 
9.9%
a 183049
 
9.7%
e 150027
 
7.9%
n 138728
 
7.3%
u 85231
 
4.5%
i 84530
 
4.5%
d 76606
 
4.0%
r 76271
 
4.0%
S 72930
 
3.8%
Other values (56) 604930
31.9%
Common
ValueCountFrequency (%)
133849
54.8%
[ 49629
 
20.3%
] 49629
 
20.3%
. 4070
 
1.7%
- 2045
 
0.8%
' 1743
 
0.7%
) 1220
 
0.5%
( 1220
 
0.5%
, 625
 
0.3%
? 107
 
< 0.1%
Other values (7) 162
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2140252
> 99.9%
None 876
 
< 0.1%
Punctuation 10
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 236676
 
11.1%
o 187861
 
8.8%
a 183049
 
8.6%
e 150027
 
7.0%
n 138728
 
6.5%
133849
 
6.3%
u 85231
 
4.0%
i 84530
 
3.9%
d 76606
 
3.6%
r 76271
 
3.6%
Other values (58) 787424
36.8%
None
ValueCountFrequency (%)
í 360
41.1%
ü 153
17.5%
é 136
 
15.5%
ã 45
 
5.1%
á 41
 
4.7%
ó 38
 
4.3%
â 32
 
3.7%
ç 25
 
2.9%
ô 15
 
1.7%
ö 9
 
1.0%
Other values (4) 22
 
2.5%
Punctuation
ValueCountFrequency (%)
10
100.0%

locality
Text

Missing 

Distinct31944
Distinct (%)10.5%
Missing34045
Missing (%)10.1%
Memory size2.6 MiB
2025-01-08T17:42:52.243698image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length312
Median length249
Mean length40.81951593
Min length3

Characters and Unicode

Total characters12411133
Distinct characters133
Distinct categories17 ?
Distinct scripts2 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4485 ?
Unique (%)1.5%

Sample

1st rowCarr Canyon, Huachuca Mountains
2nd rowSociety Islands, Moorea, In front of Hilton
3rd rowAshdown
4th rowNielamu Zhen. Route 318 between Zhangmu and Nielamu (Nyalam) ca. 8 km from Zhangmu.
5th rowMpala Research Centre
ValueCountFrequency (%)
of 95416
 
4.7%
km 27888
 
1.4%
road 25983
 
1.3%
on 20774
 
1.0%
island 19621
 
1.0%
and 19459
 
1.0%
national 18145
 
0.9%
river 17516
 
0.9%
creek 15244
 
0.8%
at 14855
 
0.7%
Other values (27242) 1755591
86.5%
2025-01-08T17:42:52.506824image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1726443
 
13.9%
a 1102256
 
8.9%
e 888496
 
7.2%
o 818946
 
6.6%
n 661740
 
5.3%
i 647279
 
5.2%
r 607431
 
4.9%
t 591988
 
4.8%
l 448950
 
3.6%
s 433370
 
3.5%
Other values (123) 4484234
36.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8489111
68.4%
Space Separator 1726443
 
13.9%
Uppercase Letter 1410083
 
11.4%
Other Punctuation 435833
 
3.5%
Decimal Number 258754
 
2.1%
Close Punctuation 32192
 
0.3%
Open Punctuation 32178
 
0.3%
Dash Punctuation 20746
 
0.2%
Other Symbol 2899
 
< 0.1%
Math Symbol 1876
 
< 0.1%
Other values (7) 1018
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 1102256
13.0%
e 888496
10.5%
o 818946
9.6%
n 661740
 
7.8%
i 647279
 
7.6%
r 607431
 
7.2%
t 591988
 
7.0%
l 448950
 
5.3%
s 433370
 
5.1%
u 303856
 
3.6%
Other values (44) 1984799
23.4%
Uppercase Letter
ValueCountFrequency (%)
S 160087
 
11.4%
C 145294
 
10.3%
M 103557
 
7.3%
B 101524
 
7.2%
R 99658
 
7.1%
P 98501
 
7.0%
N 89448
 
6.3%
I 60353
 
4.3%
A 59240
 
4.2%
L 54573
 
3.9%
Other values (24) 437848
31.1%
Other Punctuation
ValueCountFrequency (%)
, 297675
68.3%
. 103227
 
23.7%
' 10607
 
2.4%
; 7916
 
1.8%
" 4321
 
1.0%
: 4145
 
1.0%
/ 3509
 
0.8%
# 2991
 
0.7%
& 669
 
0.2%
@ 609
 
0.1%
Other values (2) 164
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 50565
19.5%
2 34503
13.3%
0 34082
13.2%
5 31120
12.0%
3 25450
9.8%
4 21075
8.1%
6 17830
 
6.9%
7 16310
 
6.3%
9 14516
 
5.6%
8 13303
 
5.1%
Math Symbol
ValueCountFrequency (%)
= 1276
68.0%
~ 431
 
23.0%
+ 123
 
6.6%
> 35
 
1.9%
< 8
 
0.4%
| 3
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 26298
81.7%
[ 5879
 
18.3%
1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 26313
81.7%
] 5879
 
18.3%
Dash Punctuation
ValueCountFrequency (%)
- 20738
> 99.9%
8
 
< 0.1%
Other Symbol
ValueCountFrequency (%)
° 2896
99.9%
3
 
0.1%
Space Separator
ValueCountFrequency (%)
1726443
100.0%
Modifier Letter
ValueCountFrequency (%)
ʻ 813
100.0%
Other Letter
ValueCountFrequency (%)
º 158
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 23
100.0%
Final Punctuation
ValueCountFrequency (%)
10
100.0%
Initial Punctuation
ValueCountFrequency (%)
6
100.0%
Other Number
ValueCountFrequency (%)
¼ 5
100.0%
Currency Symbol
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9899352
79.8%
Common 2511781
 
20.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 1102256
 
11.1%
e 888496
 
9.0%
o 818946
 
8.3%
n 661740
 
6.7%
i 647279
 
6.5%
r 607431
 
6.1%
t 591988
 
6.0%
l 448950
 
4.5%
s 433370
 
4.4%
u 303856
 
3.1%
Other values (79) 3395040
34.3%
Common
ValueCountFrequency (%)
1726443
68.7%
, 297675
 
11.9%
. 103227
 
4.1%
1 50565
 
2.0%
2 34503
 
1.4%
0 34082
 
1.4%
5 31120
 
1.2%
) 26313
 
1.0%
( 26298
 
1.0%
3 25450
 
1.0%
Other values (34) 156105
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12400051
99.9%
None 10096
 
0.1%
Modifier Letters 813
 
< 0.1%
Latin Ext Additional 142
 
< 0.1%
Punctuation 25
 
< 0.1%
Currency Symbols 3
 
< 0.1%
Letterlike Symbols 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1726443
 
13.9%
a 1102256
 
8.9%
e 888496
 
7.2%
o 818946
 
6.6%
n 661740
 
5.3%
i 647279
 
5.2%
r 607431
 
4.9%
t 591988
 
4.8%
l 448950
 
3.6%
s 433370
 
3.5%
Other values (77) 4473152
36.1%
None
ValueCountFrequency (%)
° 2896
28.7%
è 1904
18.9%
é 1026
 
10.2%
í 1025
 
10.2%
ā 813
 
8.1%
á 677
 
6.7%
ó 376
 
3.7%
ô 224
 
2.2%
ã 207
 
2.1%
ñ 167
 
1.7%
Other values (24) 781
 
7.7%
Modifier Letters
ValueCountFrequency (%)
ʻ 813
100.0%
Latin Ext Additional
ValueCountFrequency (%)
56
39.4%
56
39.4%
10
 
7.0%
10
 
7.0%
10
 
7.0%
Punctuation
ValueCountFrequency (%)
10
40.0%
8
32.0%
6
24.0%
1
 
4.0%
Currency Symbols
ValueCountFrequency (%)
3
100.0%
Letterlike Symbols
ValueCountFrequency (%)
3
100.0%

verbatimElevation
Text

Missing 

Distinct913
Distinct (%)5.7%
Missing322170
Missing (%)95.3%
Memory size2.6 MiB
2025-01-08T17:42:52.679273image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length33
Median length27
Mean length6.528761618
Min length1

Characters and Unicode

Total characters103964
Distinct characters47
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique165 ?
Unique (%)1.0%

Sample

1st row760 m
2nd row1050 ft
3rd row611 m
4th row73 m
5th row500 ft
ValueCountFrequency (%)
m 8065
23.4%
ft 7360
21.4%
ca 904
 
2.6%
503
 
1.5%
50 384
 
1.1%
3440 336
 
1.0%
sea 323
 
0.9%
level 323
 
0.9%
54 313
 
0.9%
80 302
 
0.9%
Other values (758) 15653
45.4%
2025-01-08T17:42:52.926021image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18542
17.8%
0 15801
15.2%
m 8238
 
7.9%
t 7837
 
7.5%
f 7463
 
7.2%
1 5477
 
5.3%
5 4884
 
4.7%
4 4548
 
4.4%
3 4547
 
4.4%
2 4229
 
4.1%
Other values (37) 22398
21.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 50308
48.4%
Lowercase Letter 31690
30.5%
Space Separator 18542
 
17.8%
Other Punctuation 1208
 
1.2%
Dash Punctuation 1026
 
1.0%
Uppercase Letter 596
 
0.6%
Math Symbol 364
 
0.4%
Open Punctuation 115
 
0.1%
Close Punctuation 115
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m 8238
26.0%
t 7837
24.7%
f 7463
23.6%
a 1697
 
5.4%
e 1622
 
5.1%
c 1233
 
3.9%
l 723
 
2.3%
s 424
 
1.3%
r 422
 
1.3%
v 408
 
1.3%
Other values (12) 1623
 
5.1%
Decimal Number
ValueCountFrequency (%)
0 15801
31.4%
1 5477
 
10.9%
5 4884
 
9.7%
4 4548
 
9.0%
3 4547
 
9.0%
2 4229
 
8.4%
6 3499
 
7.0%
8 3280
 
6.5%
7 2220
 
4.4%
9 1823
 
3.6%
Other Punctuation
ValueCountFrequency (%)
. 1121
92.8%
/ 70
 
5.8%
? 12
 
1.0%
' 4
 
0.3%
, 1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
S 197
33.1%
P 195
32.7%
G 195
32.7%
L 9
 
1.5%
Math Symbol
ValueCountFrequency (%)
< 294
80.8%
+ 70
 
19.2%
Space Separator
ValueCountFrequency (%)
18542
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1026
100.0%
Open Punctuation
ValueCountFrequency (%)
( 115
100.0%
Close Punctuation
ValueCountFrequency (%)
) 115
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 71678
68.9%
Latin 32286
31.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
m 8238
25.5%
t 7837
24.3%
f 7463
23.1%
a 1697
 
5.3%
e 1622
 
5.0%
c 1233
 
3.8%
l 723
 
2.2%
s 424
 
1.3%
r 422
 
1.3%
v 408
 
1.3%
Other values (16) 2219
 
6.9%
Common
ValueCountFrequency (%)
18542
25.9%
0 15801
22.0%
1 5477
 
7.6%
5 4884
 
6.8%
4 4548
 
6.3%
3 4547
 
6.3%
2 4229
 
5.9%
6 3499
 
4.9%
8 3280
 
4.6%
7 2220
 
3.1%
Other values (11) 4651
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 103964
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18542
17.8%
0 15801
15.2%
m 8238
 
7.9%
t 7837
 
7.5%
f 7463
 
7.2%
1 5477
 
5.3%
5 4884
 
4.7%
4 4548
 
4.4%
3 4547
 
4.4%
2 4229
 
4.1%
Other values (37) 22398
21.5%

verbatimDepth
Text

Missing 

Distinct59
Distinct (%)4.0%
Missing336615
Missing (%)99.6%
Memory size2.6 MiB
2025-01-08T17:42:53.018503image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length91
Median length10
Mean length8.625422583
Min length2

Characters and Unicode

Total characters12757
Distinct characters51
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)2.0%

Sample

1st rowto 1 m
2nd rowintertidal
3rd row<0.5 m
4th rowintertidal
5th rowintertidal
ValueCountFrequency (%)
intertidal 778
40.5%
m 259
 
13.5%
surface 253
 
13.2%
to 103
 
5.4%
1 95
 
4.9%
0-1 84
 
4.4%
intertida 84
 
4.4%
0.5 68
 
3.5%
1m 47
 
2.4%
cm 13
 
0.7%
Other values (55) 138
 
7.2%
2025-01-08T17:42:53.155698image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 1871
14.7%
i 1380
10.8%
e 1167
9.1%
a 1150
9.0%
r 1147
9.0%
n 891
 
7.0%
d 877
 
6.9%
l 806
 
6.3%
443
 
3.5%
I 353
 
2.8%
Other values (41) 2672
20.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10679
83.7%
Uppercase Letter 644
 
5.0%
Decimal Number 596
 
4.7%
Space Separator 443
 
3.5%
Math Symbol 161
 
1.3%
Other Punctuation 108
 
0.8%
Dash Punctuation 102
 
0.8%
Open Punctuation 12
 
0.1%
Close Punctuation 12
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 1871
17.5%
i 1380
12.9%
e 1167
10.9%
a 1150
10.8%
r 1147
10.7%
n 891
8.3%
d 877
8.2%
l 806
7.5%
m 347
 
3.2%
c 260
 
2.4%
Other values (12) 783
7.3%
Decimal Number
ValueCountFrequency (%)
1 252
42.3%
0 198
33.2%
5 82
 
13.8%
2 29
 
4.9%
3 12
 
2.0%
4 5
 
0.8%
6 5
 
0.8%
8 5
 
0.8%
9 4
 
0.7%
7 4
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
I 353
54.8%
S 258
40.1%
M 12
 
1.9%
C 10
 
1.6%
A 5
 
0.8%
U 4
 
0.6%
V 2
 
0.3%
Other Punctuation
ValueCountFrequency (%)
. 81
75.0%
: 14
 
13.0%
" 6
 
5.6%
, 4
 
3.7%
; 3
 
2.8%
Math Symbol
ValueCountFrequency (%)
< 106
65.8%
+ 36
 
22.4%
~ 19
 
11.8%
Space Separator
ValueCountFrequency (%)
443
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 102
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 11323
88.8%
Common 1434
 
11.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 1871
16.5%
i 1380
12.2%
e 1167
10.3%
a 1150
10.2%
r 1147
10.1%
n 891
7.9%
d 877
7.7%
l 806
7.1%
I 353
 
3.1%
m 347
 
3.1%
Other values (19) 1334
11.8%
Common
ValueCountFrequency (%)
443
30.9%
1 252
17.6%
0 198
13.8%
< 106
 
7.4%
- 102
 
7.1%
5 82
 
5.7%
. 81
 
5.6%
+ 36
 
2.5%
2 29
 
2.0%
~ 19
 
1.3%
Other values (12) 86
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12757
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 1871
14.7%
i 1380
10.8%
e 1167
9.1%
a 1150
9.0%
r 1147
9.0%
n 891
 
7.0%
d 877
 
6.9%
l 806
 
6.3%
443
 
3.5%
I 353
 
2.8%
Other values (41) 2672
20.9%
Distinct2
Distinct (%)100.0%
Missing338092
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:53.209304image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length40
Median length30.5
Mean length30.5
Min length21

Characters and Unicode

Total characters61
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowCarpenter, Kent E.; Williams, Jeffrey T.
2nd rowKirkbride, J. H., Jr.
ValueCountFrequency (%)
carpenter 1
10.0%
kent 1
10.0%
e 1
10.0%
williams 1
10.0%
jeffrey 1
10.0%
t 1
10.0%
kirkbride 1
10.0%
j 1
10.0%
h 1
10.0%
jr 1
10.0%
2025-01-08T17:42:53.322369image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8
13.1%
r 6
 
9.8%
e 6
 
9.8%
. 5
 
8.2%
i 4
 
6.6%
, 4
 
6.6%
J 3
 
4.9%
l 2
 
3.3%
a 2
 
3.3%
K 2
 
3.3%
Other values (16) 19
31.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 33
54.1%
Other Punctuation 10
 
16.4%
Uppercase Letter 10
 
16.4%
Space Separator 8
 
13.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 6
18.2%
e 6
18.2%
i 4
12.1%
l 2
 
6.1%
a 2
 
6.1%
f 2
 
6.1%
t 2
 
6.1%
n 2
 
6.1%
b 1
 
3.0%
k 1
 
3.0%
Other values (5) 5
15.2%
Uppercase Letter
ValueCountFrequency (%)
J 3
30.0%
K 2
20.0%
T 1
 
10.0%
C 1
 
10.0%
W 1
 
10.0%
E 1
 
10.0%
H 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
. 5
50.0%
, 4
40.0%
; 1
 
10.0%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 43
70.5%
Common 18
29.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 6
14.0%
e 6
14.0%
i 4
 
9.3%
J 3
 
7.0%
l 2
 
4.7%
a 2
 
4.7%
K 2
 
4.7%
f 2
 
4.7%
t 2
 
4.7%
n 2
 
4.7%
Other values (12) 12
27.9%
Common
ValueCountFrequency (%)
8
44.4%
. 5
27.8%
, 4
22.2%
; 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8
13.1%
r 6
 
9.8%
e 6
 
9.8%
. 5
 
8.2%
i 4
 
6.6%
, 4
 
6.6%
J 3
 
4.9%
l 2
 
3.3%
a 2
 
3.3%
K 2
 
3.3%
Other values (16) 19
31.1%

decimalLatitude
Text

Missing 

Distinct22660
Distinct (%)8.6%
Missing73462
Missing (%)21.7%
Memory size2.6 MiB
2025-01-08T17:42:53.518799image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length7
Mean length6.760010127
Min length3

Characters and Unicode

Total characters1788915
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3758 ?
Unique (%)1.4%

Sample

1st row31.434
2nd row27.5772
3rd row-17.4756
4th row28.0392
5th row0.293
ValueCountFrequency (%)
12.0832 1365
 
0.5%
16.802 1085
 
0.4%
22.0 898
 
0.3%
31.7306 892
 
0.3%
5.0 791
 
0.3%
17.4726 765
 
0.3%
38.6141 726
 
0.3%
34.9606 681
 
0.3%
17.4825 679
 
0.3%
9.82436 665
 
0.3%
Other values (22418) 256085
96.8%
2025-01-08T17:42:53.783447image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 264632
14.8%
3 225950
12.6%
1 184563
10.3%
2 163065
9.1%
7 157629
8.8%
4 151752
8.5%
8 134492
7.5%
5 130049
7.3%
6 125987
7.0%
9 108015
6.0%
Other values (2) 142781
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1471419
82.3%
Other Punctuation 264632
 
14.8%
Dash Punctuation 52864
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 225950
15.4%
1 184563
12.5%
2 163065
11.1%
7 157629
10.7%
4 151752
10.3%
8 134492
9.1%
5 130049
8.8%
6 125987
8.6%
9 108015
7.3%
0 89917
 
6.1%
Other Punctuation
ValueCountFrequency (%)
. 264632
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 52864
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1788915
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 264632
14.8%
3 225950
12.6%
1 184563
10.3%
2 163065
9.1%
7 157629
8.8%
4 151752
8.5%
8 134492
7.5%
5 130049
7.3%
6 125987
7.0%
9 108015
6.0%
Other values (2) 142781
8.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1788915
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 264632
14.8%
3 225950
12.6%
1 184563
10.3%
2 163065
9.1%
7 157629
8.8%
4 151752
8.5%
8 134492
7.5%
5 130049
7.3%
6 125987
7.0%
9 108015
6.0%
Other values (2) 142781
8.0%

decimalLongitude
Text

Missing 

Distinct21514
Distinct (%)8.1%
Missing73462
Missing (%)21.7%
Memory size2.6 MiB
2025-01-08T17:42:53.985428image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length8
Mean length7.494804105
Min length3

Characters and Unicode

Total characters1983365
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3512 ?
Unique (%)1.3%

Sample

1st row-110.285
2nd row-111.45
3rd row-149.842
4th row85.9858
5th row36.899
ValueCountFrequency (%)
68.8991 1347
 
0.5%
56.1167 1222
 
0.5%
149.826 1218
 
0.5%
88.082 1101
 
0.4%
149.775 1056
 
0.4%
110.881 910
 
0.3%
88.0817 835
 
0.3%
80.2986 742
 
0.3%
90.2589 731
 
0.3%
176.0 682
 
0.3%
Other values (21348) 254788
96.3%
2025-01-08T17:42:54.242733image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 264632
13.3%
1 242905
12.2%
- 217262
11.0%
8 175311
8.8%
7 174536
8.8%
9 158724
8.0%
6 132513
6.7%
4 129672
6.5%
2 128120
6.5%
5 123756
6.2%
Other values (2) 235934
11.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1501471
75.7%
Other Punctuation 264632
 
13.3%
Dash Punctuation 217262
 
11.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 242905
16.2%
8 175311
11.7%
7 174536
11.6%
9 158724
10.6%
6 132513
8.8%
4 129672
8.6%
2 128120
8.5%
5 123756
8.2%
3 122039
8.1%
0 113895
7.6%
Other Punctuation
ValueCountFrequency (%)
. 264632
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 217262
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1983365
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 264632
13.3%
1 242905
12.2%
- 217262
11.0%
8 175311
8.8%
7 174536
8.8%
9 158724
8.0%
6 132513
6.7%
4 129672
6.5%
2 128120
6.5%
5 123756
6.2%
Other values (2) 235934
11.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1983365
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 264632
13.3%
1 242905
12.2%
- 217262
11.0%
8 175311
8.8%
7 174536
8.8%
9 158724
8.0%
6 132513
6.7%
4 129672
6.5%
2 128120
6.5%
5 123756
6.2%
Other values (2) 235934
11.9%
Distinct453
Distinct (%)4.1%
Missing327083
Missing (%)96.7%
Memory size2.6 MiB
2025-01-08T17:42:54.430954image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.133412043
Min length3

Characters and Unicode

Total characters56524
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)0.4%

Sample

1st row500.0
2nd row500.0
3rd row140000.0
4th row100.0
5th row100.0
ValueCountFrequency (%)
100.0 1571
 
14.3%
5.0 435
 
4.0%
14.0 400
 
3.6%
12.0 386
 
3.5%
500.0 365
 
3.3%
10.0 311
 
2.8%
32.0 277
 
2.5%
200.0 273
 
2.5%
15.0 255
 
2.3%
23.0 231
 
2.1%
Other values (443) 6507
59.1%
2025-01-08T17:42:54.790883image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 17836
31.6%
. 11011
19.5%
1 6690
 
11.8%
2 4823
 
8.5%
5 3484
 
6.2%
4 3318
 
5.9%
3 2873
 
5.1%
7 1789
 
3.2%
8 1687
 
3.0%
6 1652
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 45513
80.5%
Other Punctuation 11011
 
19.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 17836
39.2%
1 6690
 
14.7%
2 4823
 
10.6%
5 3484
 
7.7%
4 3318
 
7.3%
3 2873
 
6.3%
7 1789
 
3.9%
8 1687
 
3.7%
6 1652
 
3.6%
9 1361
 
3.0%
Other Punctuation
ValueCountFrequency (%)
. 11011
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 56524
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 17836
31.6%
. 11011
19.5%
1 6690
 
11.8%
2 4823
 
8.5%
5 3484
 
6.2%
4 3318
 
5.9%
3 2873
 
5.1%
7 1789
 
3.2%
8 1687
 
3.0%
6 1652
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 56524
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 17836
31.6%
. 11011
19.5%
1 6690
 
11.8%
2 4823
 
8.5%
5 3484
 
6.2%
4 3318
 
5.9%
3 2873
 
5.1%
7 1789
 
3.2%
8 1687
 
3.0%
6 1652
 
2.9%

pointRadiusSpatialFit
Text

Missing 

Distinct4
Distinct (%)100.0%
Missing338090
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:54.851365image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters28
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row2387143
2nd row2906907
3rd row2463461
4th row2974262
ValueCountFrequency (%)
2387143 1
25.0%
2906907 1
25.0%
2463461 1
25.0%
2974262 1
25.0%
2025-01-08T17:42:54.942763image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 6
21.4%
4 4
14.3%
6 4
14.3%
3 3
10.7%
7 3
10.7%
9 3
10.7%
1 2
 
7.1%
0 2
 
7.1%
8 1
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 6
21.4%
4 4
14.3%
6 4
14.3%
3 3
10.7%
7 3
10.7%
9 3
10.7%
1 2
 
7.1%
0 2
 
7.1%
8 1
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
Common 28
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 6
21.4%
4 4
14.3%
6 4
14.3%
3 3
10.7%
7 3
10.7%
9 3
10.7%
1 2
 
7.1%
0 2
 
7.1%
8 1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 6
21.4%
4 4
14.3%
6 4
14.3%
3 3
10.7%
7 3
10.7%
9 3
10.7%
1 2
 
7.1%
0 2
 
7.1%
8 1
 
3.6%
Distinct6
Distinct (%)0.1%
Missing329029
Missing (%)97.3%
Memory size2.6 MiB
2025-01-08T17:42:54.991721image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length23
Median length23
Mean length22.7463872
Min length3

Characters and Unicode

Total characters206196
Distinct characters25
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDegrees Minutes Seconds
2nd rowDegrees Minutes Seconds
3rd rowDegrees Minutes Seconds
4th rowDegrees Minutes Seconds
5th rowDegrees Minutes Seconds
ValueCountFrequency (%)
degrees 8918
33.1%
minutes 8843
32.8%
seconds 8843
32.8%
township 107
 
0.4%
range 107
 
0.4%
decimal 75
 
0.3%
utm 24
 
0.1%
unknown 16
 
0.1%
2025-01-08T17:42:55.097500image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 44622
21.6%
s 26711
13.0%
n 17948
 
8.7%
17868
 
8.7%
g 9025
 
4.4%
i 9025
 
4.4%
D 8982
 
4.4%
o 8966
 
4.3%
c 8918
 
4.3%
r 8918
 
4.3%
Other values (15) 45213
21.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 161358
78.3%
Uppercase Letter 26970
 
13.1%
Space Separator 17868
 
8.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 44622
27.7%
s 26711
16.6%
n 17948
11.1%
g 9025
 
5.6%
i 9025
 
5.6%
o 8966
 
5.6%
c 8918
 
5.5%
r 8918
 
5.5%
d 8854
 
5.5%
u 8843
 
5.5%
Other values (8) 9528
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
D 8982
33.3%
M 8867
32.9%
S 8843
32.8%
T 131
 
0.5%
R 107
 
0.4%
U 40
 
0.1%
Space Separator
ValueCountFrequency (%)
17868
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 188328
91.3%
Common 17868
 
8.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 44622
23.7%
s 26711
14.2%
n 17948
9.5%
g 9025
 
4.8%
i 9025
 
4.8%
D 8982
 
4.8%
o 8966
 
4.8%
c 8918
 
4.7%
r 8918
 
4.7%
M 8867
 
4.7%
Other values (14) 36346
19.3%
Common
ValueCountFrequency (%)
17868
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 206196
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 44622
21.6%
s 26711
13.0%
n 17948
 
8.7%
17868
 
8.7%
g 9025
 
4.4%
i 9025
 
4.4%
D 8982
 
4.4%
o 8966
 
4.3%
c 8918
 
4.3%
r 8918
 
4.3%
Other values (15) 45213
21.9%

georeferencedBy
Text

Missing 

Distinct4
Distinct (%)100.0%
Missing338090
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:55.160300image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length40
Median length35
Mean length32.25
Min length19

Characters and Unicode

Total characters129
Distinct characters37
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowChampsodon nudivittis (Ogilby, 1895)
2nd rowCoccocypselum guianense (Aubl.) K.Schum.
3rd rowEmoia caeruleocauda (De Vis, 1892)
4th rowDimorphandra Schott
ValueCountFrequency (%)
champsodon 1
 
6.7%
nudivittis 1
 
6.7%
ogilby 1
 
6.7%
1895 1
 
6.7%
coccocypselum 1
 
6.7%
guianense 1
 
6.7%
aubl 1
 
6.7%
k.schum 1
 
6.7%
emoia 1
 
6.7%
caeruleocauda 1
 
6.7%
Other values (5) 5
33.3%
2025-01-08T17:42:55.271559image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11
 
8.5%
i 8
 
6.2%
a 8
 
6.2%
o 8
 
6.2%
c 7
 
5.4%
u 7
 
5.4%
e 6
 
4.7%
m 5
 
3.9%
s 5
 
3.9%
n 5
 
3.9%
Other values (27) 59
45.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 88
68.2%
Space Separator 11
 
8.5%
Uppercase Letter 11
 
8.5%
Decimal Number 8
 
6.2%
Other Punctuation 5
 
3.9%
Close Punctuation 3
 
2.3%
Open Punctuation 3
 
2.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 8
 
9.1%
a 8
 
9.1%
o 8
 
9.1%
c 7
 
8.0%
u 7
 
8.0%
e 6
 
6.8%
m 5
 
5.7%
s 5
 
5.7%
n 5
 
5.7%
l 4
 
4.5%
Other values (9) 25
28.4%
Uppercase Letter
ValueCountFrequency (%)
S 2
18.2%
D 2
18.2%
C 2
18.2%
A 1
9.1%
K 1
9.1%
E 1
9.1%
O 1
9.1%
V 1
9.1%
Decimal Number
ValueCountFrequency (%)
9 2
25.0%
8 2
25.0%
1 2
25.0%
5 1
12.5%
2 1
12.5%
Other Punctuation
ValueCountFrequency (%)
. 3
60.0%
, 2
40.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 99
76.7%
Common 30
 
23.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 8
 
8.1%
a 8
 
8.1%
o 8
 
8.1%
c 7
 
7.1%
u 7
 
7.1%
e 6
 
6.1%
m 5
 
5.1%
s 5
 
5.1%
n 5
 
5.1%
l 4
 
4.0%
Other values (17) 36
36.4%
Common
ValueCountFrequency (%)
11
36.7%
. 3
 
10.0%
) 3
 
10.0%
( 3
 
10.0%
9 2
 
6.7%
8 2
 
6.7%
1 2
 
6.7%
, 2
 
6.7%
5 1
 
3.3%
2 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 129
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11
 
8.5%
i 8
 
6.2%
a 8
 
6.2%
o 8
 
6.2%
c 7
 
5.4%
u 7
 
5.4%
e 6
 
4.7%
m 5
 
3.9%
s 5
 
3.9%
n 5
 
3.9%
Other values (27) 59
45.7%

georeferenceProtocol
Text

Missing 

Distinct172
Distinct (%)0.2%
Missing255273
Missing (%)75.5%
Memory size2.6 MiB
2025-01-08T17:42:55.440567image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length228
Median length12
Mean length16.00842781
Min length3

Characters and Unicode

Total characters1325834
Distinct characters69
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)< 0.1%

Sample

1st rowGoogle Earth
2nd rowGoogle Earth
3rd rowGoogle Earth
4th rowGeoLocate
5th rowGoogle Earth
ValueCountFrequency (%)
google 50688
24.4%
earth 44693
21.5%
gps 24170
 
11.6%
maps 6421
 
3.1%
georeferencing 4994
 
2.4%
and 3621
 
1.7%
pro 3250
 
1.6%
for 3177
 
1.5%
to 3177
 
1.5%
best 3176
 
1.5%
Other values (336) 60464
29.1%
2025-01-08T17:42:55.681417image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 139882
 
10.6%
125010
 
9.4%
e 116797
 
8.8%
r 91824
 
6.9%
G 90277
 
6.8%
a 86798
 
6.5%
t 72957
 
5.5%
g 60276
 
4.5%
l 58288
 
4.4%
h 52448
 
4.0%
Other values (59) 431277
32.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 892189
67.3%
Uppercase Letter 249071
 
18.8%
Space Separator 125010
 
9.4%
Other Punctuation 25668
 
1.9%
Decimal Number 24634
 
1.9%
Close Punctuation 4362
 
0.3%
Open Punctuation 4362
 
0.3%
Dash Punctuation 538
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 139882
15.7%
e 116797
13.1%
r 91824
10.3%
a 86798
9.7%
t 72957
8.2%
g 60276
6.8%
l 58288
6.5%
h 52448
 
5.9%
i 37064
 
4.2%
n 36365
 
4.1%
Other values (15) 139490
15.6%
Uppercase Letter
ValueCountFrequency (%)
G 90277
36.2%
E 47210
19.0%
P 31285
 
12.6%
S 30510
 
12.2%
M 8765
 
3.5%
N 6259
 
2.5%
C 5716
 
2.3%
I 4591
 
1.8%
B 3743
 
1.5%
W 3524
 
1.4%
Other values (13) 17191
 
6.9%
Decimal Number
ValueCountFrequency (%)
0 9139
37.1%
2 5810
23.6%
6 3901
15.8%
1 2227
 
9.0%
7 1431
 
5.8%
9 916
 
3.7%
4 561
 
2.3%
5 509
 
2.1%
3 84
 
0.3%
8 56
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 11873
46.3%
, 6280
24.5%
/ 5940
23.1%
: 1370
 
5.3%
& 153
 
0.6%
! 40
 
0.2%
; 12
 
< 0.1%
Space Separator
ValueCountFrequency (%)
125010
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4362
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4362
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 538
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1141260
86.1%
Common 184574
 
13.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 139882
12.3%
e 116797
 
10.2%
r 91824
 
8.0%
G 90277
 
7.9%
a 86798
 
7.6%
t 72957
 
6.4%
g 60276
 
5.3%
l 58288
 
5.1%
h 52448
 
4.6%
E 47210
 
4.1%
Other values (38) 324503
28.4%
Common
ValueCountFrequency (%)
125010
67.7%
. 11873
 
6.4%
0 9139
 
5.0%
, 6280
 
3.4%
/ 5940
 
3.2%
2 5810
 
3.1%
) 4362
 
2.4%
( 4362
 
2.4%
6 3901
 
2.1%
1 2227
 
1.2%
Other values (11) 5670
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1325834
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 139882
 
10.6%
125010
 
9.4%
e 116797
 
8.8%
r 91824
 
6.9%
G 90277
 
6.8%
a 86798
 
6.5%
t 72957
 
5.5%
g 60276
 
4.5%
l 58288
 
4.4%
h 52448
 
4.0%
Other values (59) 431277
32.5%

georeferenceRemarks
Text

Missing 

Distinct224
Distinct (%)2.4%
Missing328595
Missing (%)97.2%
Memory size2.6 MiB
2025-01-08T17:42:55.849261image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length83
Median length51
Mean length18.53163491
Min length2

Characters and Unicode

Total characters176032
Distinct characters63
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)0.2%

Sample

1st rowMax error (m): 100
2nd rowMax error (m): 40
3rd rowLocality extent = 1.6
4th rowLocality extent = 1 mile
5th rowMax error (m): 200
ValueCountFrequency (%)
m 5353
14.5%
max 4966
13.5%
error 4966
13.5%
1990
 
5.4%
locality 1819
 
4.9%
extent 1818
 
4.9%
100 1765
 
4.8%
50 914
 
2.5%
200 739
 
2.0%
4 668
 
1.8%
Other values (241) 11820
32.1%
2025-01-08T17:42:56.089527image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
27319
15.5%
r 16672
 
9.5%
e 10647
 
6.0%
o 10229
 
5.8%
a 10113
 
5.7%
t 9606
 
5.5%
0 8337
 
4.7%
x 7001
 
4.0%
m 6536
 
3.7%
n 5377
 
3.1%
Other values (53) 64195
36.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 94988
54.0%
Space Separator 27319
 
15.5%
Decimal Number 20310
 
11.5%
Uppercase Letter 12876
 
7.3%
Other Punctuation 8461
 
4.8%
Open Punctuation 4969
 
2.8%
Close Punctuation 4969
 
2.8%
Math Symbol 1818
 
1.0%
Dash Punctuation 322
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 16672
17.6%
e 10647
11.2%
o 10229
10.8%
a 10113
10.6%
t 9606
10.1%
x 7001
7.4%
m 6536
 
6.9%
n 5377
 
5.7%
i 4178
 
4.4%
l 2810
 
3.0%
Other values (13) 11819
12.4%
Uppercase Letter
ValueCountFrequency (%)
M 4966
38.6%
L 1894
 
14.7%
S 1112
 
8.6%
E 1102
 
8.6%
W 998
 
7.8%
G 774
 
6.0%
C 408
 
3.2%
H 372
 
2.9%
V 253
 
2.0%
R 238
 
1.8%
Other values (9) 759
 
5.9%
Decimal Number
ValueCountFrequency (%)
0 8337
41.0%
1 3655
18.0%
5 2478
 
12.2%
2 1519
 
7.5%
4 1397
 
6.9%
8 935
 
4.6%
6 713
 
3.5%
3 496
 
2.4%
7 441
 
2.2%
9 339
 
1.7%
Other Punctuation
ValueCountFrequency (%)
: 4966
58.7%
. 1937
 
22.9%
; 1213
 
14.3%
, 311
 
3.7%
/ 31
 
0.4%
' 3
 
< 0.1%
Space Separator
ValueCountFrequency (%)
27319
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4969
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4969
100.0%
Math Symbol
ValueCountFrequency (%)
= 1818
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 322
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 107864
61.3%
Common 68168
38.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 16672
15.5%
e 10647
9.9%
o 10229
9.5%
a 10113
9.4%
t 9606
8.9%
x 7001
 
6.5%
m 6536
 
6.1%
n 5377
 
5.0%
M 4966
 
4.6%
i 4178
 
3.9%
Other values (32) 22539
20.9%
Common
ValueCountFrequency (%)
27319
40.1%
0 8337
 
12.2%
( 4969
 
7.3%
) 4969
 
7.3%
: 4966
 
7.3%
1 3655
 
5.4%
5 2478
 
3.6%
. 1937
 
2.8%
= 1818
 
2.7%
2 1519
 
2.2%
Other values (11) 6201
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 176032
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
27319
15.5%
r 16672
 
9.5%
e 10647
 
6.0%
o 10229
 
5.8%
a 10113
 
5.7%
t 9606
 
5.5%
0 8337
 
4.7%
x 7001
 
4.0%
m 6536
 
3.7%
n 5377
 
3.1%
Other values (53) 64195
36.5%
Distinct4
Distinct (%)100.0%
Missing338090
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:56.166838image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length134
Median length71
Mean length83.5
Min length58

Characters and Unicode

Total characters334
Distinct characters35
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowAnimalia, Chordata, Vertebrata, Osteichthyes, Actinopterygii, Neopterygii, Acanthopterygii, Perciformes, Trachinoidei, Champsodontidae
2nd rowPlantae, Dicotyledonae, Gentianales, Rubiaceae, Rubioideae
3rd rowAnimalia, Chordata, Vertebrata, Reptilia, Squamata, Sauria, Scincidae, Eugongylinae
4th rowPlantae, Dicotyledonae, Fabales, Fabaceae, Caesalpinioideae
ValueCountFrequency (%)
animalia 2
 
7.1%
plantae 2
 
7.1%
chordata 2
 
7.1%
dicotyledonae 2
 
7.1%
vertebrata 2
 
7.1%
actinopterygii 1
 
3.6%
rubioideae 1
 
3.6%
fabaceae 1
 
3.6%
fabales 1
 
3.6%
eugongylinae 1
 
3.6%
Other values (13) 13
46.4%
2025-01-08T17:42:56.297293image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 43
12.9%
e 35
 
10.5%
i 32
 
9.6%
24
 
7.2%
, 24
 
7.2%
t 21
 
6.3%
n 16
 
4.8%
o 16
 
4.8%
r 13
 
3.9%
l 11
 
3.3%
Other values (25) 99
29.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 258
77.2%
Uppercase Letter 28
 
8.4%
Space Separator 24
 
7.2%
Other Punctuation 24
 
7.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 43
16.7%
e 35
13.6%
i 32
12.4%
t 21
8.1%
n 16
 
6.2%
o 16
 
6.2%
r 13
 
5.0%
l 11
 
4.3%
c 11
 
4.3%
d 10
 
3.9%
Other values (10) 50
19.4%
Uppercase Letter
ValueCountFrequency (%)
A 4
14.3%
C 4
14.3%
S 3
10.7%
P 3
10.7%
R 3
10.7%
D 2
7.1%
F 2
7.1%
V 2
7.1%
T 1
 
3.6%
G 1
 
3.6%
Other values (3) 3
10.7%
Space Separator
ValueCountFrequency (%)
24
100.0%
Other Punctuation
ValueCountFrequency (%)
, 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 286
85.6%
Common 48
 
14.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 43
15.0%
e 35
12.2%
i 32
11.2%
t 21
 
7.3%
n 16
 
5.6%
o 16
 
5.6%
r 13
 
4.5%
l 11
 
3.8%
c 11
 
3.8%
d 10
 
3.5%
Other values (23) 78
27.3%
Common
ValueCountFrequency (%)
24
50.0%
, 24
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 334
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 43
12.9%
e 35
 
10.5%
i 32
 
9.6%
24
 
7.2%
, 24
 
7.2%
t 21
 
6.3%
n 16
 
4.8%
o 16
 
4.8%
r 13
 
3.9%
l 11
 
3.3%
Other values (25) 99
29.6%
Distinct2
Distinct (%)50.0%
Missing338090
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:56.344558image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length7.5
Mean length7.5
Min length7

Characters and Unicode

Total characters30
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAnimalia
2nd rowPlantae
3rd rowAnimalia
4th rowPlantae
ValueCountFrequency (%)
animalia 2
50.0%
plantae 2
50.0%
2025-01-08T17:42:56.437051image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 8
26.7%
n 4
13.3%
i 4
13.3%
l 4
13.3%
A 2
 
6.7%
m 2
 
6.7%
P 2
 
6.7%
t 2
 
6.7%
e 2
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 26
86.7%
Uppercase Letter 4
 
13.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 8
30.8%
n 4
15.4%
i 4
15.4%
l 4
15.4%
m 2
 
7.7%
t 2
 
7.7%
e 2
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
A 2
50.0%
P 2
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 30
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 8
26.7%
n 4
13.3%
i 4
13.3%
l 4
13.3%
A 2
 
6.7%
m 2
 
6.7%
P 2
 
6.7%
t 2
 
6.7%
e 2
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 8
26.7%
n 4
13.3%
i 4
13.3%
l 4
13.3%
A 2
 
6.7%
m 2
 
6.7%
P 2
 
6.7%
t 2
 
6.7%
e 2
 
6.7%
Distinct2
Distinct (%)50.0%
Missing338090
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:56.483239image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10
Min length8

Characters and Unicode

Total characters40
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowChordata
2nd rowTracheophyta
3rd rowChordata
4th rowTracheophyta
ValueCountFrequency (%)
chordata 2
50.0%
tracheophyta 2
50.0%
2025-01-08T17:42:56.590661image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 8
20.0%
h 6
15.0%
o 4
10.0%
r 4
10.0%
t 4
10.0%
C 2
 
5.0%
d 2
 
5.0%
T 2
 
5.0%
c 2
 
5.0%
e 2
 
5.0%
Other values (2) 4
10.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 36
90.0%
Uppercase Letter 4
 
10.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 8
22.2%
h 6
16.7%
o 4
11.1%
r 4
11.1%
t 4
11.1%
d 2
 
5.6%
c 2
 
5.6%
e 2
 
5.6%
p 2
 
5.6%
y 2
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
C 2
50.0%
T 2
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 40
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 8
20.0%
h 6
15.0%
o 4
10.0%
r 4
10.0%
t 4
10.0%
C 2
 
5.0%
d 2
 
5.0%
T 2
 
5.0%
c 2
 
5.0%
e 2
 
5.0%
Other values (2) 4
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 8
20.0%
h 6
15.0%
o 4
10.0%
r 4
10.0%
t 4
10.0%
C 2
 
5.0%
d 2
 
5.0%
T 2
 
5.0%
c 2
 
5.0%
e 2
 
5.0%
Other values (2) 4
10.0%
Distinct2
Distinct (%)66.7%
Missing338091
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:56.636652image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length11.33333333
Min length8

Characters and Unicode

Total characters34
Distinct characters15
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st rowMagnoliopsida
2nd rowSquamata
3rd rowMagnoliopsida
ValueCountFrequency (%)
magnoliopsida 2
66.7%
squamata 1
33.3%
2025-01-08T17:42:56.732545image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 7
20.6%
o 4
11.8%
i 4
11.8%
M 2
 
5.9%
g 2
 
5.9%
n 2
 
5.9%
l 2
 
5.9%
p 2
 
5.9%
s 2
 
5.9%
d 2
 
5.9%
Other values (5) 5
14.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 31
91.2%
Uppercase Letter 3
 
8.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 7
22.6%
o 4
12.9%
i 4
12.9%
g 2
 
6.5%
n 2
 
6.5%
l 2
 
6.5%
p 2
 
6.5%
s 2
 
6.5%
d 2
 
6.5%
q 1
 
3.2%
Other values (3) 3
9.7%
Uppercase Letter
ValueCountFrequency (%)
M 2
66.7%
S 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 34
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 7
20.6%
o 4
11.8%
i 4
11.8%
M 2
 
5.9%
g 2
 
5.9%
n 2
 
5.9%
l 2
 
5.9%
p 2
 
5.9%
s 2
 
5.9%
d 2
 
5.9%
Other values (5) 5
14.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 7
20.6%
o 4
11.8%
i 4
11.8%
M 2
 
5.9%
g 2
 
5.9%
n 2
 
5.9%
l 2
 
5.9%
p 2
 
5.9%
s 2
 
5.9%
d 2
 
5.9%
Other values (5) 5
14.7%
Distinct3
Distinct (%)100.0%
Missing338091
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:56.777544image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length11
Median length11
Mean length9.666666667
Min length7

Characters and Unicode

Total characters29
Distinct characters16
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st rowPerciformes
2nd rowGentianales
3rd rowFabales
ValueCountFrequency (%)
perciformes 1
33.3%
gentianales 1
33.3%
fabales 1
33.3%
2025-01-08T17:42:56.881489image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 5
17.2%
a 4
13.8%
s 3
10.3%
r 2
 
6.9%
i 2
 
6.9%
n 2
 
6.9%
l 2
 
6.9%
P 1
 
3.4%
c 1
 
3.4%
f 1
 
3.4%
Other values (6) 6
20.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 26
89.7%
Uppercase Letter 3
 
10.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 5
19.2%
a 4
15.4%
s 3
11.5%
r 2
 
7.7%
i 2
 
7.7%
n 2
 
7.7%
l 2
 
7.7%
c 1
 
3.8%
f 1
 
3.8%
o 1
 
3.8%
Other values (3) 3
11.5%
Uppercase Letter
ValueCountFrequency (%)
P 1
33.3%
G 1
33.3%
F 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 29
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 5
17.2%
a 4
13.8%
s 3
10.3%
r 2
 
6.9%
i 2
 
6.9%
n 2
 
6.9%
l 2
 
6.9%
P 1
 
3.4%
c 1
 
3.4%
f 1
 
3.4%
Other values (6) 6
20.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 5
17.2%
a 4
13.8%
s 3
10.3%
r 2
 
6.9%
i 2
 
6.9%
n 2
 
6.9%
l 2
 
6.9%
P 1
 
3.4%
c 1
 
3.4%
f 1
 
3.4%
Other values (6) 6
20.7%
Distinct4
Distinct (%)100.0%
Missing338090
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:56.928597image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length15
Median length12
Mean length10.25
Min length8

Characters and Unicode

Total characters41
Distinct characters18
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowChampsodontidae
2nd rowRubiaceae
3rd rowScincidae
4th rowFabaceae
ValueCountFrequency (%)
champsodontidae 1
25.0%
rubiaceae 1
25.0%
scincidae 1
25.0%
fabaceae 1
25.0%
2025-01-08T17:42:57.034372image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 8
19.5%
e 6
14.6%
c 4
9.8%
i 4
9.8%
d 3
 
7.3%
b 2
 
4.9%
o 2
 
4.9%
n 2
 
4.9%
C 1
 
2.4%
R 1
 
2.4%
Other values (8) 8
19.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 37
90.2%
Uppercase Letter 4
 
9.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 8
21.6%
e 6
16.2%
c 4
10.8%
i 4
10.8%
d 3
 
8.1%
b 2
 
5.4%
o 2
 
5.4%
n 2
 
5.4%
u 1
 
2.7%
t 1
 
2.7%
Other values (4) 4
10.8%
Uppercase Letter
ValueCountFrequency (%)
C 1
25.0%
R 1
25.0%
S 1
25.0%
F 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 41
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 8
19.5%
e 6
14.6%
c 4
9.8%
i 4
9.8%
d 3
 
7.3%
b 2
 
4.9%
o 2
 
4.9%
n 2
 
4.9%
C 1
 
2.4%
R 1
 
2.4%
Other values (8) 8
19.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 8
19.5%
e 6
14.6%
c 4
9.8%
i 4
9.8%
d 3
 
7.3%
b 2
 
4.9%
o 2
 
4.9%
n 2
 
4.9%
C 1
 
2.4%
R 1
 
2.4%
Other values (8) 8
19.5%
Distinct4
Distinct (%)100.0%
Missing338090
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:57.082373image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length11
Mean length10
Min length5

Characters and Unicode

Total characters40
Distinct characters18
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowChampsodon
2nd rowCoccocypselum
3rd rowEmoia
4th rowDimorphandra
ValueCountFrequency (%)
champsodon 1
25.0%
coccocypselum 1
25.0%
emoia 1
25.0%
dimorphandra 1
25.0%
2025-01-08T17:42:57.191510image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 6
15.0%
a 4
 
10.0%
m 4
 
10.0%
c 3
 
7.5%
p 3
 
7.5%
n 2
 
5.0%
i 2
 
5.0%
h 2
 
5.0%
C 2
 
5.0%
d 2
 
5.0%
Other values (8) 10
25.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 36
90.0%
Uppercase Letter 4
 
10.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 6
16.7%
a 4
11.1%
m 4
11.1%
c 3
8.3%
p 3
8.3%
n 2
 
5.6%
i 2
 
5.6%
h 2
 
5.6%
d 2
 
5.6%
s 2
 
5.6%
Other values (5) 6
16.7%
Uppercase Letter
ValueCountFrequency (%)
C 2
50.0%
E 1
25.0%
D 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 40
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 6
15.0%
a 4
 
10.0%
m 4
 
10.0%
c 3
 
7.5%
p 3
 
7.5%
n 2
 
5.0%
i 2
 
5.0%
h 2
 
5.0%
C 2
 
5.0%
d 2
 
5.0%
Other values (8) 10
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 6
15.0%
a 4
 
10.0%
m 4
 
10.0%
c 3
 
7.5%
p 3
 
7.5%
n 2
 
5.0%
i 2
 
5.0%
h 2
 
5.0%
C 2
 
5.0%
d 2
 
5.0%
Other values (8) 10
25.0%
Distinct4
Distinct (%)100.0%
Missing338090
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:57.240273image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length11
Mean length10
Min length5

Characters and Unicode

Total characters40
Distinct characters18
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowChampsodon
2nd rowCoccocypselum
3rd rowEmoia
4th rowDimorphandra
ValueCountFrequency (%)
champsodon 1
25.0%
coccocypselum 1
25.0%
emoia 1
25.0%
dimorphandra 1
25.0%
2025-01-08T17:42:57.352510image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 6
15.0%
a 4
 
10.0%
m 4
 
10.0%
c 3
 
7.5%
p 3
 
7.5%
n 2
 
5.0%
i 2
 
5.0%
h 2
 
5.0%
C 2
 
5.0%
d 2
 
5.0%
Other values (8) 10
25.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 36
90.0%
Uppercase Letter 4
 
10.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 6
16.7%
a 4
11.1%
m 4
11.1%
c 3
8.3%
p 3
8.3%
n 2
 
5.6%
i 2
 
5.6%
h 2
 
5.6%
d 2
 
5.6%
s 2
 
5.6%
Other values (5) 6
16.7%
Uppercase Letter
ValueCountFrequency (%)
C 2
50.0%
E 1
25.0%
D 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 40
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 6
15.0%
a 4
 
10.0%
m 4
 
10.0%
c 3
 
7.5%
p 3
 
7.5%
n 2
 
5.0%
i 2
 
5.0%
h 2
 
5.0%
C 2
 
5.0%
d 2
 
5.0%
Other values (8) 10
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 6
15.0%
a 4
 
10.0%
m 4
 
10.0%
c 3
 
7.5%
p 3
 
7.5%
n 2
 
5.0%
i 2
 
5.0%
h 2
 
5.0%
C 2
 
5.0%
d 2
 
5.0%
Other values (8) 10
25.0%

member
Text

Missing 

Distinct3
Distinct (%)100.0%
Missing338091
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:57.402689image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length10
Mean length10.66666667
Min length9

Characters and Unicode

Total characters32
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st rownudivittis
2nd rowguianense
3rd rowcaeruleocauda
ValueCountFrequency (%)
nudivittis 1
33.3%
guianense 1
33.3%
caeruleocauda 1
33.3%
2025-01-08T17:42:57.510670image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
u 4
12.5%
i 4
12.5%
a 4
12.5%
e 4
12.5%
n 3
9.4%
d 2
6.2%
t 2
6.2%
s 2
6.2%
c 2
6.2%
v 1
 
3.1%
Other values (4) 4
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 32
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 4
12.5%
i 4
12.5%
a 4
12.5%
e 4
12.5%
n 3
9.4%
d 2
6.2%
t 2
6.2%
s 2
6.2%
c 2
6.2%
v 1
 
3.1%
Other values (4) 4
12.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 32
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
u 4
12.5%
i 4
12.5%
a 4
12.5%
e 4
12.5%
n 3
9.4%
d 2
6.2%
t 2
6.2%
s 2
6.2%
c 2
6.2%
v 1
 
3.1%
Other values (4) 4
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
u 4
12.5%
i 4
12.5%
a 4
12.5%
e 4
12.5%
n 3
9.4%
d 2
6.2%
t 2
6.2%
s 2
6.2%
c 2
6.2%
v 1
 
3.1%
Other values (4) 4
12.5%
Distinct2
Distinct (%)50.0%
Missing338090
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:57.556169image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.5
Min length5

Characters and Unicode

Total characters26
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)25.0%

Sample

1st rowSPECIES
2nd rowSPECIES
3rd rowSPECIES
4th rowGENUS
ValueCountFrequency (%)
species 3
75.0%
genus 1
 
25.0%
2025-01-08T17:42:57.660998image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 7
26.9%
E 7
26.9%
P 3
11.5%
C 3
11.5%
I 3
11.5%
G 1
 
3.8%
N 1
 
3.8%
U 1
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 26
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 7
26.9%
E 7
26.9%
P 3
11.5%
C 3
11.5%
I 3
11.5%
G 1
 
3.8%
N 1
 
3.8%
U 1
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 26
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 7
26.9%
E 7
26.9%
P 3
11.5%
C 3
11.5%
I 3
11.5%
G 1
 
3.8%
N 1
 
3.8%
U 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 7
26.9%
E 7
26.9%
P 3
11.5%
C 3
11.5%
I 3
11.5%
G 1
 
3.8%
N 1
 
3.8%
U 1
 
3.8%
Distinct16
Distinct (%)0.3%
Missing333028
Missing (%)98.5%
Memory size2.6 MiB
2025-01-08T17:42:57.709715image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.255823135
Min length2

Characters and Unicode

Total characters26626
Distinct characters22
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowaff.
2nd rowcf.
3rd rowaff.
4th rowuncertain
5th rowuncertain
ValueCountFrequency (%)
cf 2738
53.8%
uncertain 1858
36.5%
aff 320
 
6.3%
near 75
 
1.5%
complex 38
 
0.7%
sp 16
 
0.3%
group 12
 
0.2%
n 10
 
0.2%
nov 6
 
0.1%
s.l 5
 
0.1%
Other values (2) 9
 
0.2%
2025-01-08T17:42:57.816033image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
c 4628
17.4%
n 3807
14.3%
f 3378
12.7%
. 2728
10.2%
a 2237
8.4%
e 1976
7.4%
r 1945
7.3%
t 1858
7.0%
i 1858
7.0%
u 1842
 
6.9%
Other values (12) 369
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 23827
89.5%
Other Punctuation 2728
 
10.2%
Uppercase Letter 50
 
0.2%
Space Separator 21
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 4628
19.4%
n 3807
16.0%
f 3378
14.2%
a 2237
9.4%
e 1976
8.3%
r 1945
8.2%
t 1858
7.8%
i 1858
7.8%
u 1842
 
7.7%
p 66
 
0.3%
Other values (7) 232
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
U 28
56.0%
A 16
32.0%
C 6
 
12.0%
Other Punctuation
ValueCountFrequency (%)
. 2728
100.0%
Space Separator
ValueCountFrequency (%)
21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 23877
89.7%
Common 2749
 
10.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 4628
19.4%
n 3807
15.9%
f 3378
14.1%
a 2237
9.4%
e 1976
8.3%
r 1945
8.1%
t 1858
7.8%
i 1858
7.8%
u 1842
 
7.7%
p 66
 
0.3%
Other values (10) 282
 
1.2%
Common
ValueCountFrequency (%)
. 2728
99.2%
21
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26626
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
c 4628
17.4%
n 3807
14.3%
f 3378
12.7%
. 2728
10.2%
a 2237
8.4%
e 1976
7.4%
r 1945
7.3%
t 1858
7.0%
i 1858
7.0%
u 1842
 
6.9%
Other values (12) 369
 
1.4%

typeStatus
Text

Missing 

Distinct10
Distinct (%)0.2%
Missing331537
Missing (%)98.1%
Memory size2.6 MiB
2025-01-08T17:42:57.860748image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length8
Mean length8.010370596
Min length4

Characters and Unicode

Total characters52524
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPARATYPE
2nd rowPARATYPE
3rd rowPARATYPE
4th rowPARATYPE
5th rowPARATYPE
ValueCountFrequency (%)
paratype 5817
88.7%
holotype 330
 
5.0%
paralectotype 125
 
1.9%
cotype 86
 
1.3%
syntype 76
 
1.2%
type 73
 
1.1%
allotype 23
 
0.4%
neotype 13
 
0.2%
topotype 10
 
0.2%
isotype 4
 
0.1%
2025-01-08T17:42:57.958140image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
P 12509
23.8%
A 11907
22.7%
E 6695
12.7%
T 6692
12.7%
Y 6633
12.6%
R 5942
11.3%
O 931
 
1.8%
L 501
 
1.0%
H 330
 
0.6%
C 211
 
0.4%
Other values (3) 173
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 52524
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
P 12509
23.8%
A 11907
22.7%
E 6695
12.7%
T 6692
12.7%
Y 6633
12.6%
R 5942
11.3%
O 931
 
1.8%
L 501
 
1.0%
H 330
 
0.6%
C 211
 
0.4%
Other values (3) 173
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 52524
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
P 12509
23.8%
A 11907
22.7%
E 6695
12.7%
T 6692
12.7%
Y 6633
12.6%
R 5942
11.3%
O 931
 
1.8%
L 501
 
1.0%
H 330
 
0.6%
C 211
 
0.4%
Other values (3) 173
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52524
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P 12509
23.8%
A 11907
22.7%
E 6695
12.7%
T 6692
12.7%
Y 6633
12.6%
R 5942
11.3%
O 931
 
1.8%
L 501
 
1.0%
H 330
 
0.6%
C 211
 
0.4%
Other values (3) 173
 
0.3%

identifiedBy
Text

Missing 

Distinct1866
Distinct (%)1.7%
Missing226045
Missing (%)66.9%
Memory size2.6 MiB
2025-01-08T17:42:58.129959image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length150
Median length128
Mean length39.12826531
Min length2

Characters and Unicode

Total characters4384283
Distinct characters83
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique200 ?
Unique (%)0.2%

Sample

1st rowAnker, Arthur
2nd rowOsborn, Karen J., (IZ), Smithsonian Institution - National Museum of Natural History (UNITED STATES)
3rd rowBaldwin, Carole C.
4th rowHobbs, Horton H., Jr., Smithsonian Institution, National Museum of Natural History
5th rowPaulay, Gustav, University of Florida (UNITED STATES)
ValueCountFrequency (%)
united 36040
 
5.8%
states 35997
 
5.8%
of 27839
 
4.5%
smithsonian 24345
 
3.9%
22476
 
3.6%
institution 20514
 
3.3%
national 18658
 
3.0%
museum 17521
 
2.8%
natural 17241
 
2.8%
history 17162
 
2.8%
Other values (2280) 384193
61.8%
2025-01-08T17:42:58.383582image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
509937
 
11.6%
i 263018
 
6.0%
a 259974
 
5.9%
t 236702
 
5.4%
n 236587
 
5.4%
o 217618
 
5.0%
e 199155
 
4.5%
, 179169
 
4.1%
r 173333
 
4.0%
s 169593
 
3.9%
Other values (73) 1939197
44.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2458529
56.1%
Uppercase Letter 993786
22.7%
Space Separator 509937
 
11.6%
Other Punctuation 274091
 
6.3%
Close Punctuation 61757
 
1.4%
Open Punctuation 61757
 
1.4%
Dash Punctuation 23898
 
0.5%
Decimal Number 518
 
< 0.1%
Initial Punctuation 5
 
< 0.1%
Final Punctuation 5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 263018
10.7%
a 259974
10.6%
t 236702
9.6%
n 236587
9.6%
o 217618
8.9%
e 199155
8.1%
r 173333
 
7.1%
s 169593
 
6.9%
l 137018
 
5.6%
u 122655
 
5.0%
Other values (27) 442876
18.0%
Uppercase Letter
ValueCountFrequency (%)
T 131779
13.3%
S 126036
12.7%
E 89193
 
9.0%
N 81500
 
8.2%
I 69915
 
7.0%
A 68248
 
6.9%
D 60242
 
6.1%
U 50332
 
5.1%
M 44673
 
4.5%
B 34085
 
3.4%
Other values (18) 237783
23.9%
Other Punctuation
ValueCountFrequency (%)
, 179169
65.4%
. 89197
32.5%
; 4445
 
1.6%
' 576
 
0.2%
& 430
 
0.2%
/ 274
 
0.1%
Decimal Number
ValueCountFrequency (%)
2 148
28.6%
4 74
14.3%
6 74
14.3%
0 74
14.3%
1 74
14.3%
9 74
14.3%
Space Separator
ValueCountFrequency (%)
509937
100.0%
Close Punctuation
ValueCountFrequency (%)
) 61757
100.0%
Open Punctuation
ValueCountFrequency (%)
( 61757
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23898
100.0%
Initial Punctuation
ValueCountFrequency (%)
5
100.0%
Final Punctuation
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3452315
78.7%
Common 931968
 
21.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 263018
 
7.6%
a 259974
 
7.5%
t 236702
 
6.9%
n 236587
 
6.9%
o 217618
 
6.3%
e 199155
 
5.8%
r 173333
 
5.0%
s 169593
 
4.9%
l 137018
 
4.0%
T 131779
 
3.8%
Other values (55) 1427538
41.4%
Common
ValueCountFrequency (%)
509937
54.7%
, 179169
 
19.2%
. 89197
 
9.6%
) 61757
 
6.6%
( 61757
 
6.6%
- 23898
 
2.6%
; 4445
 
0.5%
' 576
 
0.1%
& 430
 
< 0.1%
/ 274
 
< 0.1%
Other values (8) 528
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4383750
> 99.9%
None 523
 
< 0.1%
Punctuation 10
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
509937
 
11.6%
i 263018
 
6.0%
a 259974
 
5.9%
t 236702
 
5.4%
n 236587
 
5.4%
o 217618
 
5.0%
e 199155
 
4.5%
, 179169
 
4.1%
r 173333
 
4.0%
s 169593
 
3.9%
Other values (58) 1938664
44.2%
None
ValueCountFrequency (%)
í 212
40.5%
ö 128
24.5%
á 99
18.9%
ø 29
 
5.5%
ú 26
 
5.0%
ó 12
 
2.3%
Ø 7
 
1.3%
ë 3
 
0.6%
è 3
 
0.6%
ñ 1
 
0.2%
Other values (3) 3
 
0.6%
Punctuation
ValueCountFrequency (%)
5
50.0%
5
50.0%

identifiedByID
Text

Constant  Missing 

Distinct1
Distinct (%)25.0%
Missing338090
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:58.436011image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters32
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowACCEPTED
2nd rowACCEPTED
3rd rowACCEPTED
4th rowACCEPTED
ValueCountFrequency (%)
accepted 4
100.0%
2025-01-08T17:42:58.524579image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 8
25.0%
E 8
25.0%
A 4
12.5%
P 4
12.5%
T 4
12.5%
D 4
12.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 32
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 8
25.0%
E 8
25.0%
A 4
12.5%
P 4
12.5%
T 4
12.5%
D 4
12.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 32
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 8
25.0%
E 8
25.0%
A 4
12.5%
P 4
12.5%
T 4
12.5%
D 4
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
C 8
25.0%
E 8
25.0%
A 4
12.5%
P 4
12.5%
T 4
12.5%
D 4
12.5%

identificationVerificationStatus
Text

Constant  Missing 

Distinct1
Distinct (%)25.0%
Missing338090
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:58.575091image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

Total characters144
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row26098c25-8f7f-4c71-97ac-1d3db181c65e
2nd row26098c25-8f7f-4c71-97ac-1d3db181c65e
3rd row26098c25-8f7f-4c71-97ac-1d3db181c65e
4th row26098c25-8f7f-4c71-97ac-1d3db181c65e
ValueCountFrequency (%)
26098c25-8f7f-4c71-97ac-1d3db181c65e 4
100.0%
2025-01-08T17:42:58.672440image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
11.1%
c 16
11.1%
- 16
11.1%
8 12
 
8.3%
7 12
 
8.3%
2 8
 
5.6%
6 8
 
5.6%
d 8
 
5.6%
f 8
 
5.6%
5 8
 
5.6%
Other values (7) 32
22.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 84
58.3%
Lowercase Letter 44
30.6%
Dash Punctuation 16
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
19.0%
8 12
14.3%
7 12
14.3%
2 8
9.5%
6 8
9.5%
5 8
9.5%
9 8
9.5%
4 4
 
4.8%
0 4
 
4.8%
3 4
 
4.8%
Lowercase Letter
ValueCountFrequency (%)
c 16
36.4%
d 8
18.2%
f 8
18.2%
a 4
 
9.1%
b 4
 
9.1%
e 4
 
9.1%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 100
69.4%
Latin 44
30.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
16.0%
- 16
16.0%
8 12
12.0%
7 12
12.0%
2 8
8.0%
6 8
8.0%
5 8
8.0%
9 8
8.0%
4 4
 
4.0%
0 4
 
4.0%
Latin
ValueCountFrequency (%)
c 16
36.4%
d 8
18.2%
f 8
18.2%
a 4
 
9.1%
b 4
 
9.1%
e 4
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 144
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
11.1%
c 16
11.1%
- 16
11.1%
8 12
 
8.3%
7 12
 
8.3%
2 8
 
5.6%
6 8
 
5.6%
d 8
 
5.6%
f 8
 
5.6%
5 8
 
5.6%
Other values (7) 32
22.2%

identificationRemarks
Text

Constant  Missing 

Distinct1
Distinct (%)25.0%
Missing338090
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:58.710087image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters8
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUS
2nd rowUS
3rd rowUS
4th rowUS
ValueCountFrequency (%)
us 4
100.0%
2025-01-08T17:42:58.799084image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 4
50.0%
S 4
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 8
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U 4
50.0%
S 4
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U 4
50.0%
S 4
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U 4
50.0%
S 4
50.0%

taxonID
Text

Missing 

Distinct4
Distinct (%)100.0%
Missing338090
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:58.850073image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters96
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row2024-12-01T12:07:17.508Z
2nd row2024-12-01T12:07:28.759Z
3rd row2024-12-01T12:07:38.231Z
4th row2024-12-01T12:07:36.611Z
ValueCountFrequency (%)
2024-12-01t12:07:17.508z 1
25.0%
2024-12-01t12:07:28.759z 1
25.0%
2024-12-01t12:07:38.231z 1
25.0%
2024-12-01t12:07:36.611z 1
25.0%
2025-01-08T17:42:58.949187image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 18
18.8%
1 16
16.7%
0 13
13.5%
- 8
8.3%
: 8
8.3%
7 6
 
6.2%
4 4
 
4.2%
T 4
 
4.2%
. 4
 
4.2%
Z 4
 
4.2%
Other values (5) 11
11.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
70.8%
Other Punctuation 12
 
12.5%
Dash Punctuation 8
 
8.3%
Uppercase Letter 8
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 18
26.5%
1 16
23.5%
0 13
19.1%
7 6
 
8.8%
4 4
 
5.9%
8 3
 
4.4%
3 3
 
4.4%
5 2
 
2.9%
6 2
 
2.9%
9 1
 
1.5%
Other Punctuation
ValueCountFrequency (%)
: 8
66.7%
. 4
33.3%
Uppercase Letter
ValueCountFrequency (%)
T 4
50.0%
Z 4
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 88
91.7%
Latin 8
 
8.3%

Most frequent character per script

Common
ValueCountFrequency (%)
2 18
20.5%
1 16
18.2%
0 13
14.8%
- 8
9.1%
: 8
9.1%
7 6
 
6.8%
4 4
 
4.5%
. 4
 
4.5%
8 3
 
3.4%
3 3
 
3.4%
Other values (3) 5
 
5.7%
Latin
ValueCountFrequency (%)
T 4
50.0%
Z 4
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 18
18.8%
1 16
16.7%
0 13
13.5%
- 8
8.3%
: 8
8.3%
7 6
 
6.2%
4 4
 
4.2%
T 4
 
4.2%
. 4
 
4.2%
Z 4
 
4.2%
Other values (5) 11
11.5%

scientificNameID
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing338092
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:58.990186image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters10
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row940.5
2nd row651.0
ValueCountFrequency (%)
940.5 1
50.0%
651.0 1
50.0%
2025-01-08T17:42:59.077613image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2
20.0%
. 2
20.0%
5 2
20.0%
9 1
10.0%
4 1
10.0%
6 1
10.0%
1 1
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8
80.0%
Other Punctuation 2
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2
25.0%
5 2
25.0%
9 1
12.5%
4 1
12.5%
6 1
12.5%
1 1
12.5%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2
20.0%
. 2
20.0%
5 2
20.0%
9 1
10.0%
4 1
10.0%
6 1
10.0%
1 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2
20.0%
. 2
20.0%
5 2
20.0%
9 1
10.0%
4 1
10.0%
6 1
10.0%
1 1
10.0%

acceptedNameUsageID
Text

Missing 

Distinct44952
Distinct (%)13.5%
Missing6111
Missing (%)1.8%
Memory size2.6 MiB
2025-01-08T17:42:59.269036image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length7
Mean length6.770428004
Min length1

Characters and Unicode

Total characters2247667
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9418 ?
Unique (%)2.8%

Sample

1st row10583418
2nd row5854277
3rd row5771
4th row4479
5th row2651085
ValueCountFrequency (%)
6841 3252
 
1.0%
637 2297
 
0.7%
2285664 2008
 
0.6%
2329589 2006
 
0.6%
2440447 1919
 
0.6%
8324617 1660
 
0.5%
8770992 1474
 
0.4%
2431491 1334
 
0.4%
2307333 1035
 
0.3%
68 875
 
0.3%
Other values (44942) 314123
94.6%
2025-01-08T17:42:59.535431image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 335749
14.9%
1 273500
12.2%
4 233904
10.4%
3 226967
10.1%
5 207520
9.2%
7 206909
9.2%
8 206081
9.2%
9 198048
8.8%
0 180588
8.0%
6 178400
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2247666
> 99.9%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 335749
14.9%
1 273500
12.2%
4 233904
10.4%
3 226967
10.1%
5 207520
9.2%
7 206909
9.2%
8 206081
9.2%
9 198048
8.8%
0 180588
8.0%
6 178400
7.9%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2247667
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 335749
14.9%
1 273500
12.2%
4 233904
10.4%
3 226967
10.1%
5 207520
9.2%
7 206909
9.2%
8 206081
9.2%
9 198048
8.8%
0 180588
8.0%
6 178400
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2247667
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 335749
14.9%
1 273500
12.2%
4 233904
10.4%
3 226967
10.1%
5 207520
9.2%
7 206909
9.2%
8 206081
9.2%
9 198048
8.8%
0 180588
8.0%
6 178400
7.9%

namePublishedInID
Text

Missing 

Distinct3
Distinct (%)75.0%
Missing338090
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:42:59.605474image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length104
Median length92.5
Mean length60.25
Min length28

Characters and Unicode

Total characters241
Distinct characters21
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st rowGEODETIC_DATUM_ASSUMED_WGS84;GEODETIC_DATUM_INVALID;CONTINENT_DERIVED_FROM_COORDINATES;CONTINENT_INVALID
2nd rowGEODETIC_DATUM_ASSUMED_WGS84
3rd rowGEODETIC_DATUM_ASSUMED_WGS84;CONTINENT_DERIVED_FROM_COORDINATES;CONTINENT_INVALID
4th rowGEODETIC_DATUM_ASSUMED_WGS84
ValueCountFrequency (%)
geodetic_datum_assumed_wgs84 2
50.0%
geodetic_datum_assumed_wgs84;geodetic_datum_invalid;continent_derived_from_coordinates;continent_invalid 1
25.0%
geodetic_datum_assumed_wgs84;continent_derived_from_coordinates;continent_invalid 1
25.0%
2025-01-08T17:42:59.832151image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 24
 
10.0%
D 23
 
9.5%
_ 22
 
9.1%
T 20
 
8.3%
I 19
 
7.9%
N 17
 
7.1%
O 15
 
6.2%
S 14
 
5.8%
A 14
 
5.8%
M 11
 
4.6%
Other values (11) 62
25.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 206
85.5%
Connector Punctuation 22
 
9.1%
Decimal Number 8
 
3.3%
Other Punctuation 5
 
2.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 24
11.7%
D 23
11.2%
T 20
9.7%
I 19
9.2%
N 17
8.3%
O 15
 
7.3%
S 14
 
6.8%
A 14
 
6.8%
M 11
 
5.3%
C 11
 
5.3%
Other values (7) 38
18.4%
Decimal Number
ValueCountFrequency (%)
8 4
50.0%
4 4
50.0%
Connector Punctuation
ValueCountFrequency (%)
_ 22
100.0%
Other Punctuation
ValueCountFrequency (%)
; 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 206
85.5%
Common 35
 
14.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 24
11.7%
D 23
11.2%
T 20
9.7%
I 19
9.2%
N 17
8.3%
O 15
 
7.3%
S 14
 
6.8%
A 14
 
6.8%
M 11
 
5.3%
C 11
 
5.3%
Other values (7) 38
18.4%
Common
ValueCountFrequency (%)
_ 22
62.9%
; 5
 
14.3%
8 4
 
11.4%
4 4
 
11.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 241
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 24
 
10.0%
D 23
 
9.5%
_ 22
 
9.1%
T 20
 
8.3%
I 19
 
7.9%
N 17
 
7.1%
O 15
 
6.2%
S 14
 
5.8%
A 14
 
5.8%
M 11
 
4.6%
Other values (11) 62
25.7%
Distinct45747
Distinct (%)13.5%
Missing1
Missing (%)< 0.1%
Memory size2.6 MiB
2025-01-08T17:43:00.021406image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length136
Median length95
Mean length30.8157785
Min length4

Characters and Unicode

Total characters10418599
Distinct characters107
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9824 ?
Unique (%)2.9%

Sample

1st rowRectiostoma fernaldella
2nd rowSiboglinidae
3rd rowAmphinomidae
4th rowCambaridae
5th rowPolystichum Roth
ValueCountFrequency (%)
37261
 
3.0%
linnaeus 10150
 
0.8%
1758 7990
 
0.6%
l 6159
 
0.5%
sedis 6107
 
0.5%
incertae 6107
 
0.5%
1985 5118
 
0.4%
plethodon 4673
 
0.4%
orconectes 4548
 
0.4%
walker 4503
 
0.4%
Other values (49822) 1170241
92.7%
2025-01-08T17:43:00.289691image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
924764
 
8.9%
a 838089
 
8.0%
e 687702
 
6.6%
i 638989
 
6.1%
r 539087
 
5.2%
s 536232
 
5.1%
o 513067
 
4.9%
n 469039
 
4.5%
l 423628
 
4.1%
t 373559
 
3.6%
Other values (97) 4474443
42.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7079014
67.9%
Decimal Number 1044964
 
10.0%
Space Separator 924764
 
8.9%
Uppercase Letter 742652
 
7.1%
Other Punctuation 379610
 
3.6%
Close Punctuation 121557
 
1.2%
Open Punctuation 121557
 
1.2%
Dash Punctuation 4400
 
< 0.1%
Math Symbol 78
 
< 0.1%
Connector Punctuation 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 838089
11.8%
e 687702
9.7%
i 638989
 
9.0%
r 539087
 
7.6%
s 536232
 
7.6%
o 513067
 
7.2%
n 469039
 
6.6%
l 423628
 
6.0%
t 373559
 
5.3%
u 350709
 
5.0%
Other values (43) 1708913
24.1%
Uppercase Letter
ValueCountFrequency (%)
P 65610
 
8.8%
C 64603
 
8.7%
B 58305
 
7.9%
S 57140
 
7.7%
L 52829
 
7.1%
M 49682
 
6.7%
H 47964
 
6.5%
A 47366
 
6.4%
G 43295
 
5.8%
D 38406
 
5.2%
Other values (24) 217452
29.3%
Decimal Number
ValueCountFrequency (%)
1 307079
29.4%
8 201736
19.3%
9 143440
13.7%
7 71902
 
6.9%
2 62368
 
6.0%
0 62111
 
5.9%
5 60348
 
5.8%
6 50547
 
4.8%
3 46539
 
4.5%
4 38894
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 266361
70.2%
. 75661
 
19.9%
& 37261
 
9.8%
' 327
 
0.1%
Space Separator
ValueCountFrequency (%)
924764
100.0%
Close Punctuation
ValueCountFrequency (%)
) 121557
100.0%
Open Punctuation
ValueCountFrequency (%)
( 121557
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4400
100.0%
Math Symbol
ValueCountFrequency (%)
× 78
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7821666
75.1%
Common 2596933
 
24.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 838089
 
10.7%
e 687702
 
8.8%
i 638989
 
8.2%
r 539087
 
6.9%
s 536232
 
6.9%
o 513067
 
6.6%
n 469039
 
6.0%
l 423628
 
5.4%
t 373559
 
4.8%
u 350709
 
4.5%
Other values (77) 2451565
31.3%
Common
ValueCountFrequency (%)
924764
35.6%
1 307079
 
11.8%
, 266361
 
10.3%
8 201736
 
7.8%
9 143440
 
5.5%
) 121557
 
4.7%
( 121557
 
4.7%
. 75661
 
2.9%
7 71902
 
2.8%
2 62368
 
2.4%
Other values (10) 300508
 
11.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10395423
99.8%
None 23176
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
924764
 
8.9%
a 838089
 
8.1%
e 687702
 
6.6%
i 638989
 
6.1%
r 539087
 
5.2%
s 536232
 
5.2%
o 513067
 
4.9%
n 469039
 
4.5%
l 423628
 
4.1%
t 373559
 
3.6%
Other values (61) 4451267
42.8%
None
ValueCountFrequency (%)
ü 7909
34.1%
é 6134
26.5%
è 2353
 
10.2%
ö 1884
 
8.1%
å 1557
 
6.7%
ä 858
 
3.7%
ó 719
 
3.1%
á 407
 
1.8%
ø 314
 
1.4%
É 261
 
1.1%
Other values (26) 780
 
3.4%

acceptedNameUsage
Text

Constant  Missing 

Distinct1
Distinct (%)25.0%
Missing338090
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:43:00.341193image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters20
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowfalse
2nd rowfalse
3rd rowfalse
4th rowfalse
ValueCountFrequency (%)
false 4
100.0%
2025-01-08T17:43:00.426535image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
f 4
20.0%
a 4
20.0%
l 4
20.0%
s 4
20.0%
e 4
20.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 20
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
f 4
20.0%
a 4
20.0%
l 4
20.0%
s 4
20.0%
e 4
20.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
f 4
20.0%
a 4
20.0%
l 4
20.0%
s 4
20.0%
e 4
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
f 4
20.0%
a 4
20.0%
l 4
20.0%
s 4
20.0%
e 4
20.0%

parentNameUsage
Text

Missing 

Distinct4
Distinct (%)100.0%
Missing338090
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:43:00.472535image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters28
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row2387143
2nd row2906907
3rd row2463461
4th row2974262
ValueCountFrequency (%)
2387143 1
25.0%
2906907 1
25.0%
2463461 1
25.0%
2974262 1
25.0%
2025-01-08T17:43:00.571549image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 6
21.4%
4 4
14.3%
6 4
14.3%
3 3
10.7%
7 3
10.7%
9 3
10.7%
1 2
 
7.1%
0 2
 
7.1%
8 1
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 6
21.4%
4 4
14.3%
6 4
14.3%
3 3
10.7%
7 3
10.7%
9 3
10.7%
1 2
 
7.1%
0 2
 
7.1%
8 1
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
Common 28
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 6
21.4%
4 4
14.3%
6 4
14.3%
3 3
10.7%
7 3
10.7%
9 3
10.7%
1 2
 
7.1%
0 2
 
7.1%
8 1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 6
21.4%
4 4
14.3%
6 4
14.3%
3 3
10.7%
7 3
10.7%
9 3
10.7%
1 2
 
7.1%
0 2
 
7.1%
8 1
 
3.6%

originalNameUsage
Text

Missing 

Distinct4
Distinct (%)100.0%
Missing338090
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:43:00.621235image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters28
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row2387143
2nd row2906907
3rd row2463461
4th row2974262
ValueCountFrequency (%)
2387143 1
25.0%
2906907 1
25.0%
2463461 1
25.0%
2974262 1
25.0%
2025-01-08T17:43:00.719836image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 6
21.4%
4 4
14.3%
6 4
14.3%
3 3
10.7%
7 3
10.7%
9 3
10.7%
1 2
 
7.1%
0 2
 
7.1%
8 1
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 6
21.4%
4 4
14.3%
6 4
14.3%
3 3
10.7%
7 3
10.7%
9 3
10.7%
1 2
 
7.1%
0 2
 
7.1%
8 1
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
Common 28
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 6
21.4%
4 4
14.3%
6 4
14.3%
3 3
10.7%
7 3
10.7%
9 3
10.7%
1 2
 
7.1%
0 2
 
7.1%
8 1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 6
21.4%
4 4
14.3%
6 4
14.3%
3 3
10.7%
7 3
10.7%
9 3
10.7%
1 2
 
7.1%
0 2
 
7.1%
8 1
 
3.6%

nameAccordingTo
Text

Missing 

Distinct2
Distinct (%)50.0%
Missing338090
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:43:00.763214image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row6
3rd row1
4th row6
ValueCountFrequency (%)
1 2
50.0%
6 2
50.0%
2025-01-08T17:43:00.848938image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
50.0%
6 2
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
50.0%
6 2
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
50.0%
6 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
50.0%
6 2
50.0%

namePublishedIn
Text

Missing 

Distinct2
Distinct (%)50.0%
Missing338090
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:43:00.888938image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length4.5
Mean length4.5
Min length2

Characters and Unicode

Total characters18
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row44
2nd row7707728
3rd row44
4th row7707728
ValueCountFrequency (%)
44 2
50.0%
7707728 2
50.0%
2025-01-08T17:43:00.980653image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 8
44.4%
4 4
22.2%
0 2
 
11.1%
2 2
 
11.1%
8 2
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 8
44.4%
4 4
22.2%
0 2
 
11.1%
2 2
 
11.1%
8 2
 
11.1%

Most occurring scripts

ValueCountFrequency (%)
Common 18
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 8
44.4%
4 4
22.2%
0 2
 
11.1%
2 2
 
11.1%
8 2
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 8
44.4%
4 4
22.2%
0 2
 
11.1%
2 2
 
11.1%
8 2
 
11.1%

namePublishedInYear
Text

Missing 

Distinct2
Distinct (%)66.7%
Missing338091
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:43:01.020430image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length3
Mean length4.666666667
Min length3

Characters and Unicode

Total characters14
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st row220
2nd row11592253
3rd row220
ValueCountFrequency (%)
220 2
66.7%
11592253 1
33.3%
2025-01-08T17:43:01.111721image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 6
42.9%
0 2
 
14.3%
1 2
 
14.3%
5 2
 
14.3%
9 1
 
7.1%
3 1
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 6
42.9%
0 2
 
14.3%
1 2
 
14.3%
5 2
 
14.3%
9 1
 
7.1%
3 1
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
Common 14
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 6
42.9%
0 2
 
14.3%
1 2
 
14.3%
5 2
 
14.3%
9 1
 
7.1%
3 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 6
42.9%
0 2
 
14.3%
1 2
 
14.3%
5 2
 
14.3%
9 1
 
7.1%
3 1
 
7.1%

higherClassification
Text

Missing 

Distinct4818
Distinct (%)1.5%
Missing5891
Missing (%)1.7%
Memory size2.6 MiB
2025-01-08T17:43:01.285558image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length162
Median length142
Mean length76.55919724
Min length3

Characters and Unicode

Total characters25433195
Distinct characters73
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique462 ?
Unique (%)0.1%

Sample

1st rowAnimalia, Arthropoda, Insecta, Lepidoptera, Depressariidae, Stenomatinae
2nd rowAnimalia, Annelida, Polychaeta, Sedentaria, Canalipalpata, Sabellida, Siboglinidae
3rd rowAnimalia, Annelida, Polychaeta, Errantia, Amphinomida, Amphinomidae
4th rowAnimalia, Arthropoda, Crustacea, Malacostraca, Eumalacostraca, Eucarida, Decapoda, Pleocyemata, Cambaridae
5th rowPlantae, Pteridophyte, Polypodiales, Dryopteridaceae
ValueCountFrequency (%)
animalia 287414
 
13.0%
arthropoda 145732
 
6.6%
insecta 113112
 
5.1%
chordata 103438
 
4.7%
vertebrata 102398
 
4.6%
lepidoptera 79682
 
3.6%
actinopterygii 40707
 
1.8%
osteichthyes 40705
 
1.8%
neopterygii 40702
 
1.8%
plantae 35513
 
1.6%
Other values (5331) 1219943
55.2%
2025-01-08T17:43:01.551027image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 3309102
13.0%
i 2169092
 
8.5%
e 2151600
 
8.5%
1877143
 
7.4%
, 1874867
 
7.4%
t 1538441
 
6.0%
r 1525223
 
6.0%
o 1481338
 
5.8%
n 1000711
 
3.9%
d 933466
 
3.7%
Other values (63) 7572212
29.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 19468705
76.5%
Uppercase Letter 2207029
 
8.7%
Other Punctuation 1878709
 
7.4%
Space Separator 1877143
 
7.4%
Open Punctuation 715
 
< 0.1%
Close Punctuation 715
 
< 0.1%
Dash Punctuation 127
 
< 0.1%
Decimal Number 40
 
< 0.1%
Connector Punctuation 12
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 3309102
17.0%
i 2169092
11.1%
e 2151600
11.1%
t 1538441
7.9%
r 1525223
7.8%
o 1481338
7.6%
n 1000711
 
5.1%
d 933466
 
4.8%
l 864491
 
4.4%
c 812570
 
4.2%
Other values (17) 3682671
18.9%
Uppercase Letter
ValueCountFrequency (%)
A 616321
27.9%
C 270051
12.2%
P 208229
 
9.4%
M 124908
 
5.7%
I 120801
 
5.5%
E 116755
 
5.3%
L 112347
 
5.1%
V 112031
 
5.1%
S 86356
 
3.9%
D 72265
 
3.3%
Other values (16) 366965
16.6%
Decimal Number
ValueCountFrequency (%)
6 9
22.5%
1 8
20.0%
0 7
17.5%
3 7
17.5%
9 3
 
7.5%
7 2
 
5.0%
4 1
 
2.5%
2 1
 
2.5%
5 1
 
2.5%
8 1
 
2.5%
Other Punctuation
ValueCountFrequency (%)
, 1874867
99.8%
. 3842
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 679
95.0%
[ 36
 
5.0%
Close Punctuation
ValueCountFrequency (%)
) 679
95.0%
] 36
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
124
97.6%
- 3
 
2.4%
Space Separator
ValueCountFrequency (%)
1877143
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 21675734
85.2%
Common 3757461
 
14.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 3309102
15.3%
i 2169092
 
10.0%
e 2151600
 
9.9%
t 1538441
 
7.1%
r 1525223
 
7.0%
o 1481338
 
6.8%
n 1000711
 
4.6%
d 933466
 
4.3%
l 864491
 
4.0%
c 812570
 
3.7%
Other values (43) 5889700
27.2%
Common
ValueCountFrequency (%)
1877143
50.0%
, 1874867
49.9%
. 3842
 
0.1%
( 679
 
< 0.1%
) 679
 
< 0.1%
124
 
< 0.1%
[ 36
 
< 0.1%
] 36
 
< 0.1%
_ 12
 
< 0.1%
6 9
 
< 0.1%
Other values (10) 34
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25433053
> 99.9%
Punctuation 124
 
< 0.1%
None 18
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 3309102
13.0%
i 2169092
 
8.5%
e 2151600
 
8.5%
1877143
 
7.4%
, 1874867
 
7.4%
t 1538441
 
6.0%
r 1525223
 
6.0%
o 1481338
 
5.8%
n 1000711
 
3.9%
d 933466
 
3.7%
Other values (61) 7572070
29.8%
Punctuation
ValueCountFrequency (%)
124
100.0%
None
ValueCountFrequency (%)
ö 18
100.0%
Distinct10
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size2.6 MiB
2025-01-08T17:43:01.609030image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length14
Median length8
Mean length8.009370203
Min length4

Characters and Unicode

Total characters2707912
Distinct characters28
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st rowAnimalia
2nd rowAnimalia
3rd rowAnimalia
4th rowAnimalia
5th rowPlantae
ValueCountFrequency (%)
animalia 291926
84.8%
plantae 35530
 
10.3%
incertae 6107
 
1.8%
sedis 6107
 
1.8%
chromista 3038
 
0.9%
bacteria 1166
 
0.3%
fungi 322
 
0.1%
8518 1
 
< 0.1%
8798 1
 
< 0.1%
9115 1
 
< 0.1%
2025-01-08T17:43:01.713876image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 666389
24.6%
i 600592
22.2%
n 333885
12.3%
l 327456
12.1%
m 294964
10.9%
A 291926
10.8%
e 55017
 
2.0%
t 45841
 
1.7%
P 35530
 
1.3%
s 15252
 
0.6%
Other values (18) 41060
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2369807
87.5%
Uppercase Letter 331982
 
12.3%
Space Separator 6107
 
0.2%
Decimal Number 16
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 666389
28.1%
i 600592
25.3%
n 333885
14.1%
l 327456
13.8%
m 294964
12.4%
e 55017
 
2.3%
t 45841
 
1.9%
s 15252
 
0.6%
r 10311
 
0.4%
c 7273
 
0.3%
Other values (5) 12827
 
0.5%
Decimal Number
ValueCountFrequency (%)
8 5
31.2%
5 3
18.8%
1 3
18.8%
9 2
 
12.5%
7 1
 
6.2%
3 1
 
6.2%
6 1
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
A 291926
87.9%
P 35530
 
10.7%
C 3038
 
0.9%
B 1166
 
0.4%
F 322
 
0.1%
Space Separator
ValueCountFrequency (%)
6107
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2701789
99.8%
Common 6123
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 666389
24.7%
i 600592
22.2%
n 333885
12.4%
l 327456
12.1%
m 294964
10.9%
A 291926
10.8%
e 55017
 
2.0%
t 45841
 
1.7%
P 35530
 
1.3%
s 15252
 
0.6%
Other values (10) 34937
 
1.3%
Common
ValueCountFrequency (%)
6107
99.7%
8 5
 
0.1%
5 3
 
< 0.1%
1 3
 
< 0.1%
9 2
 
< 0.1%
7 1
 
< 0.1%
3 1
 
< 0.1%
6 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2707912
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 666389
24.6%
i 600592
22.2%
n 333885
12.3%
l 327456
12.1%
m 294964
10.9%
A 291926
10.8%
e 55017
 
2.0%
t 45841
 
1.7%
P 35530
 
1.3%
s 15252
 
0.6%
Other values (18) 41060
 
1.5%

phylum
Text

Missing 

Distinct44
Distinct (%)< 0.1%
Missing6808
Missing (%)2.0%
Memory size2.6 MiB
2025-01-08T17:43:01.769447image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length15
Median length14
Mean length9.353480075
Min length7

Characters and Unicode

Total characters3098677
Distinct characters45
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)< 0.1%

Sample

1st rowArthropoda
2nd rowAnnelida
3rd rowAnnelida
4th rowArthropoda
5th rowTracheophyta
ValueCountFrequency (%)
arthropoda 145971
44.1%
chordata 103372
31.2%
tracheophyta 30584
 
9.2%
mollusca 20737
 
6.3%
annelida 11327
 
3.4%
cnidaria 3177
 
1.0%
rhodophyta 2942
 
0.9%
myzozoa 2110
 
0.6%
echinodermata 1630
 
0.5%
chlorophyta 1622
 
0.5%
Other values (34) 7814
 
2.4%
2025-01-08T17:43:01.889742image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 473882
15.3%
o 469081
15.1%
r 439672
14.2%
h 325528
10.5%
t 292348
9.4%
d 269484
8.7%
p 182549
 
5.9%
A 157354
 
5.1%
C 109510
 
3.5%
l 56397
 
1.8%
Other values (35) 322872
10.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2767367
89.3%
Uppercase Letter 331282
 
10.7%
Decimal Number 28
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 473882
17.1%
o 469081
17.0%
r 439672
15.9%
h 325528
11.8%
t 292348
10.6%
d 269484
9.7%
p 182549
 
6.6%
l 56397
 
2.0%
c 56157
 
2.0%
e 51319
 
1.9%
Other values (10) 150950
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
A 157354
47.5%
C 109510
33.1%
T 30585
 
9.2%
M 22851
 
6.9%
R 2943
 
0.9%
P 2127
 
0.6%
E 1668
 
0.5%
N 1361
 
0.4%
B 1257
 
0.4%
O 847
 
0.3%
Other values (6) 779
 
0.2%
Decimal Number
ValueCountFrequency (%)
2 7
25.0%
7 4
14.3%
4 3
10.7%
6 3
10.7%
3 3
10.7%
0 2
 
7.1%
9 2
 
7.1%
8 2
 
7.1%
1 2
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 3098649
> 99.9%
Common 28
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 473882
15.3%
o 469081
15.1%
r 439672
14.2%
h 325528
10.5%
t 292348
9.4%
d 269484
8.7%
p 182549
 
5.9%
A 157354
 
5.1%
C 109510
 
3.5%
l 56397
 
1.8%
Other values (26) 322844
10.4%
Common
ValueCountFrequency (%)
2 7
25.0%
7 4
14.3%
4 3
10.7%
6 3
10.7%
3 3
10.7%
0 2
 
7.1%
9 2
 
7.1%
8 2
 
7.1%
1 2
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3098677
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 473882
15.3%
o 469081
15.1%
r 439672
14.2%
h 325528
10.5%
t 292348
9.4%
d 269484
8.7%
p 182549
 
5.9%
A 157354
 
5.1%
C 109510
 
3.5%
l 56397
 
1.8%
Other values (35) 322872
10.4%

class
Text

Missing 

Distinct105
Distinct (%)< 0.1%
Missing52277
Missing (%)15.5%
Memory size2.6 MiB
2025-01-08T17:43:01.986719image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length18
Mean length8.708561772
Min length4

Characters and Unicode

Total characters2489055
Distinct characters44
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st rowInsecta
2nd rowPolychaeta
3rd rowPolychaeta
4th rowMalacostraca
5th rowPolypodiopsida
ValueCountFrequency (%)
insecta 112951
39.5%
malacostraca 27895
 
9.8%
mammalia 24478
 
8.6%
amphibia 18384
 
6.4%
magnoliopsida 15795
 
5.5%
liliopsida 10876
 
3.8%
polychaeta 10686
 
3.7%
bivalvia 9771
 
3.4%
gastropoda 9525
 
3.3%
squamata 9481
 
3.3%
Other values (95) 35975
 
12.6%
2025-01-08T17:43:02.147745image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 486650
19.6%
s 193470
 
7.8%
c 193177
 
7.8%
t 177830
 
7.1%
i 170083
 
6.8%
e 160201
 
6.4%
o 142892
 
5.7%
n 138528
 
5.6%
l 116613
 
4.7%
I 112951
 
4.5%
Other values (34) 596660
24.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2203238
88.5%
Uppercase Letter 285817
 
11.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 486650
22.1%
s 193470
 
8.8%
c 193177
 
8.8%
t 177830
 
8.1%
i 170083
 
7.7%
e 160201
 
7.3%
o 142892
 
6.5%
n 138528
 
6.3%
l 116613
 
5.3%
m 81034
 
3.7%
Other values (14) 342760
15.6%
Uppercase Letter
ValueCountFrequency (%)
I 112951
39.5%
M 69115
24.2%
A 32386
 
11.3%
P 15849
 
5.5%
L 11211
 
3.9%
G 10243
 
3.6%
S 9874
 
3.5%
B 9817
 
3.4%
C 3459
 
1.2%
F 2942
 
1.0%
Other values (10) 7970
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 2489055
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 486650
19.6%
s 193470
 
7.8%
c 193177
 
7.8%
t 177830
 
7.1%
i 170083
 
6.8%
e 160201
 
6.4%
o 142892
 
5.7%
n 138528
 
5.6%
l 116613
 
4.7%
I 112951
 
4.5%
Other values (34) 596660
24.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2489055
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 486650
19.6%
s 193470
 
7.8%
c 193177
 
7.8%
t 177830
 
7.1%
i 170083
 
6.8%
e 160201
 
6.4%
o 142892
 
5.7%
n 138528
 
5.6%
l 116613
 
4.7%
I 112951
 
4.5%
Other values (34) 596660
24.0%

order
Text

Missing 

Distinct534
Distinct (%)0.2%
Missing30344
Missing (%)9.0%
Memory size2.6 MiB
2025-01-08T17:43:02.316180image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length20
Median length19
Mean length9.980555646
Min length5

Characters and Unicode

Total characters3071516
Distinct characters59
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)< 0.1%

Sample

1st rowLepidoptera
2nd rowSabellida
3rd rowAmphinomida
4th rowDecapoda
5th rowPolypodiales
ValueCountFrequency (%)
lepidoptera 79519
25.8%
perciformes 25783
 
8.4%
decapoda 23755
 
7.7%
coleoptera 10132
 
3.3%
anura 10009
 
3.3%
hymenoptera 8496
 
2.8%
rodentia 8406
 
2.7%
caudata 8204
 
2.7%
poales 7858
 
2.6%
cetacea 7808
 
2.5%
Other values (524) 117780
38.3%
2025-01-08T17:43:02.557958image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 434314
14.1%
a 364271
11.9%
o 268279
 
8.7%
r 262893
 
8.6%
p 253174
 
8.2%
i 238211
 
7.8%
t 176177
 
5.7%
d 167228
 
5.4%
s 113822
 
3.7%
l 95900
 
3.1%
Other values (49) 697247
22.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2763748
90.0%
Uppercase Letter 307747
 
10.0%
Decimal Number 21
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 434314
15.7%
a 364271
13.2%
o 268279
9.7%
r 262893
9.5%
p 253174
9.2%
i 238211
8.6%
t 176177
6.4%
d 167228
 
6.1%
s 113822
 
4.1%
l 95900
 
3.5%
Other values (16) 389479
14.1%
Uppercase Letter
ValueCountFrequency (%)
L 85088
27.6%
P 48522
15.8%
C 41463
13.5%
D 32883
 
10.7%
A 26001
 
8.4%
H 14781
 
4.8%
S 14644
 
4.8%
R 10170
 
3.3%
M 7556
 
2.5%
V 5610
 
1.8%
Other values (14) 21029
 
6.8%
Decimal Number
ValueCountFrequency (%)
2 3
14.3%
6 3
14.3%
3 3
14.3%
4 3
14.3%
9 2
9.5%
0 2
9.5%
7 2
9.5%
1 2
9.5%
8 1
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 3071495
> 99.9%
Common 21
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 434314
14.1%
a 364271
11.9%
o 268279
 
8.7%
r 262893
 
8.6%
p 253174
 
8.2%
i 238211
 
7.8%
t 176177
 
5.7%
d 167228
 
5.4%
s 113822
 
3.7%
l 95900
 
3.1%
Other values (40) 697226
22.7%
Common
ValueCountFrequency (%)
2 3
14.3%
6 3
14.3%
3 3
14.3%
4 3
14.3%
9 2
9.5%
0 2
9.5%
7 2
9.5%
1 2
9.5%
8 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3071516
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 434314
14.1%
a 364271
11.9%
o 268279
 
8.7%
r 262893
 
8.6%
p 253174
 
8.2%
i 238211
 
7.8%
t 176177
 
5.7%
d 167228
 
5.4%
s 113822
 
3.7%
l 95900
 
3.1%
Other values (49) 697247
22.7%

superfamily
Text

Missing 

Distinct3
Distinct (%)100.0%
Missing338091
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:43:02.624462image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length23
Median length21
Mean length21
Min length19

Characters and Unicode

Total characters63
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st rowChampsodon nudivittis
2nd rowCoccocypselum guianense
3rd rowEmoia caeruleocauda
ValueCountFrequency (%)
champsodon 1
16.7%
nudivittis 1
16.7%
coccocypselum 1
16.7%
guianense 1
16.7%
emoia 1
16.7%
caeruleocauda 1
16.7%
2025-01-08T17:43:02.740344image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 6
 
9.5%
o 6
 
9.5%
u 5
 
7.9%
e 5
 
7.9%
i 5
 
7.9%
c 5
 
7.9%
s 4
 
6.3%
n 4
 
6.3%
m 3
 
4.8%
d 3
 
4.8%
Other values (11) 17
27.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 57
90.5%
Space Separator 3
 
4.8%
Uppercase Letter 3
 
4.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 6
10.5%
o 6
10.5%
u 5
8.8%
e 5
8.8%
i 5
8.8%
c 5
8.8%
s 4
 
7.0%
n 4
 
7.0%
m 3
 
5.3%
d 3
 
5.3%
Other values (8) 11
19.3%
Uppercase Letter
ValueCountFrequency (%)
C 2
66.7%
E 1
33.3%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 60
95.2%
Common 3
 
4.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 6
10.0%
o 6
10.0%
u 5
 
8.3%
e 5
 
8.3%
i 5
 
8.3%
c 5
 
8.3%
s 4
 
6.7%
n 4
 
6.7%
m 3
 
5.0%
d 3
 
5.0%
Other values (10) 14
23.3%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 6
 
9.5%
o 6
 
9.5%
u 5
 
7.9%
e 5
 
7.9%
i 5
 
7.9%
c 5
 
7.9%
s 4
 
6.3%
n 4
 
6.3%
m 3
 
4.8%
d 3
 
4.8%
Other values (11) 17
27.0%

family
Text

Missing 

Distinct3097
Distinct (%)1.0%
Missing19906
Missing (%)5.9%
Memory size2.6 MiB
2025-01-08T17:43:02.852569image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length40
Median length20
Mean length10.83802029
Min length6

Characters and Unicode

Total characters3448528
Distinct characters62
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique312 ?
Unique (%)0.1%

Sample

1st rowDepressariidae
2nd rowSiboglinidae
3rd rowAmphinomidae
4th rowCambaridae
5th rowDryopteridaceae
ValueCountFrequency (%)
cambaridae 12102
 
3.8%
geometridae 12012
 
3.8%
noctuidae 7500
 
2.4%
tortricidae 7246
 
2.3%
plethodontidae 6784
 
2.1%
poaceae 6677
 
2.1%
delphinidae 5540
 
1.7%
erebidae 5452
 
1.7%
siboglinidae 5009
 
1.6%
vesicomyidae 4930
 
1.5%
Other values (3098) 244947
77.0%
2025-01-08T17:43:03.036611image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 525485
15.2%
a 509708
14.8%
i 440350
12.8%
d 317748
9.2%
r 191641
 
5.6%
o 190413
 
5.5%
c 139936
 
4.1%
t 125374
 
3.6%
l 122376
 
3.5%
n 101480
 
2.9%
Other values (52) 784017
22.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3130303
90.8%
Uppercase Letter 318195
 
9.2%
Space Separator 11
 
< 0.1%
Decimal Number 8
 
< 0.1%
Other Punctuation 5
 
< 0.1%
Open Punctuation 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 525485
16.8%
a 509708
16.3%
i 440350
14.1%
d 317748
10.2%
r 191641
 
6.1%
o 190413
 
6.1%
c 139936
 
4.5%
t 125374
 
4.0%
l 122376
 
3.9%
n 101480
 
3.2%
Other values (16) 465792
14.9%
Uppercase Letter
ValueCountFrequency (%)
C 53292
16.7%
P 43342
13.6%
G 29396
9.2%
S 26858
8.4%
A 22868
 
7.2%
T 18614
 
5.8%
M 18061
 
5.7%
D 16080
 
5.1%
L 13747
 
4.3%
N 12781
 
4.0%
Other values (16) 63156
19.8%
Decimal Number
ValueCountFrequency (%)
1 2
25.0%
8 2
25.0%
9 2
25.0%
2 1
12.5%
5 1
12.5%
Other Punctuation
ValueCountFrequency (%)
. 3
60.0%
, 2
40.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3448498
> 99.9%
Common 30
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 525485
15.2%
a 509708
14.8%
i 440350
12.8%
d 317748
9.2%
r 191641
 
5.6%
o 190413
 
5.5%
c 139936
 
4.1%
t 125374
 
3.6%
l 122376
 
3.5%
n 101480
 
2.9%
Other values (42) 783987
22.7%
Common
ValueCountFrequency (%)
11
36.7%
( 3
 
10.0%
. 3
 
10.0%
) 3
 
10.0%
, 2
 
6.7%
1 2
 
6.7%
8 2
 
6.7%
9 2
 
6.7%
2 1
 
3.3%
5 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3448528
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 525485
15.2%
a 509708
14.8%
i 440350
12.8%
d 317748
9.2%
r 191641
 
5.6%
o 190413
 
5.5%
c 139936
 
4.1%
t 125374
 
3.6%
l 122376
 
3.5%
n 101480
 
2.9%
Other values (52) 784017
22.7%

subfamily
Text

Missing 

Distinct4
Distinct (%)100.0%
Missing338090
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:43:03.100612image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length23
Median length20
Mean length19.75
Min length16

Characters and Unicode

Total characters79
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowChampsodon nudivittis
2nd rowCoccocypselum guianense
3rd rowEmoia caeruleocauda
4th rowDimorphandra sp.
ValueCountFrequency (%)
champsodon 1
12.5%
nudivittis 1
12.5%
coccocypselum 1
12.5%
guianense 1
12.5%
emoia 1
12.5%
caeruleocauda 1
12.5%
dimorphandra 1
12.5%
sp 1
12.5%
2025-01-08T17:43:03.213687image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 8
 
10.1%
o 7
 
8.9%
i 6
 
7.6%
c 5
 
6.3%
s 5
 
6.3%
n 5
 
6.3%
u 5
 
6.3%
e 5
 
6.3%
m 4
 
5.1%
p 4
 
5.1%
Other values (13) 25
31.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 70
88.6%
Space Separator 4
 
5.1%
Uppercase Letter 4
 
5.1%
Other Punctuation 1
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 8
11.4%
o 7
10.0%
i 6
 
8.6%
c 5
 
7.1%
s 5
 
7.1%
n 5
 
7.1%
u 5
 
7.1%
e 5
 
7.1%
m 4
 
5.7%
p 4
 
5.7%
Other values (8) 16
22.9%
Uppercase Letter
ValueCountFrequency (%)
C 2
50.0%
E 1
25.0%
D 1
25.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 74
93.7%
Common 5
 
6.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 8
 
10.8%
o 7
 
9.5%
i 6
 
8.1%
c 5
 
6.8%
s 5
 
6.8%
n 5
 
6.8%
u 5
 
6.8%
e 5
 
6.8%
m 4
 
5.4%
p 4
 
5.4%
Other values (11) 20
27.0%
Common
ValueCountFrequency (%)
4
80.0%
. 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 79
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 8
 
10.1%
o 7
 
8.9%
i 6
 
7.6%
c 5
 
6.3%
s 5
 
6.3%
n 5
 
6.3%
u 5
 
6.3%
e 5
 
6.3%
m 4
 
5.1%
p 4
 
5.1%
Other values (13) 25
31.6%

subtribe
Text

Constant  Missing 

Distinct1
Distinct (%)25.0%
Missing338090
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:43:03.255223image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters12
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEML
2nd rowEML
3rd rowEML
4th rowEML
ValueCountFrequency (%)
eml 4
100.0%
2025-01-08T17:43:03.339541image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 4
33.3%
M 4
33.3%
L 4
33.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 12
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 4
33.3%
M 4
33.3%
L 4
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 12
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 4
33.3%
M 4
33.3%
L 4
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 4
33.3%
M 4
33.3%
L 4
33.3%

genus
Text

Missing 

Distinct19311
Distinct (%)6.4%
Missing34392
Missing (%)10.2%
Memory size2.6 MiB
2025-01-08T17:43:03.527126image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length19
Mean length9.330027461
Min length3

Characters and Unicode

Total characters2833548
Distinct characters65
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2143 ?
Unique (%)0.7%

Sample

1st rowRectiostoma
2nd rowPolystichum
3rd rowMesontoplatys
4th rowDulcerana
5th rowAmanses
ValueCountFrequency (%)
plethodon 4671
 
1.5%
faxonius 4236
 
1.4%
procambarus 3675
 
1.2%
bathymodiolus 2587
 
0.9%
riftia 2006
 
0.7%
tursiops 1919
 
0.6%
cambarus 1707
 
0.6%
delphinus 1662
 
0.5%
aegla 1424
 
0.5%
anolis 1420
 
0.5%
Other values (19301) 278395
91.7%
2025-01-08T17:43:03.774223image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 312625
 
11.0%
o 247355
 
8.7%
i 219282
 
7.7%
s 204987
 
7.2%
e 199721
 
7.0%
r 183312
 
6.5%
t 142209
 
5.0%
l 138064
 
4.9%
n 131110
 
4.6%
u 127288
 
4.5%
Other values (55) 927595
32.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2529740
89.3%
Uppercase Letter 303712
 
10.7%
Decimal Number 68
 
< 0.1%
Dash Punctuation 16
 
< 0.1%
Other Punctuation 12
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 312625
12.4%
o 247355
 
9.8%
i 219282
 
8.7%
s 204987
 
8.1%
e 199721
 
7.9%
r 183312
 
7.2%
t 142209
 
5.6%
l 138064
 
5.5%
n 131110
 
5.2%
u 127288
 
5.0%
Other values (16) 623787
24.7%
Uppercase Letter
ValueCountFrequency (%)
P 46871
15.4%
C 36089
11.9%
A 32417
10.7%
S 23721
 
7.8%
M 19100
 
6.3%
E 17748
 
5.8%
L 15962
 
5.3%
H 15384
 
5.1%
T 14009
 
4.6%
D 13393
 
4.4%
Other values (16) 69018
22.7%
Decimal Number
ValueCountFrequency (%)
2 18
26.5%
1 16
23.5%
0 13
19.1%
7 6
 
8.8%
4 4
 
5.9%
3 3
 
4.4%
8 3
 
4.4%
5 2
 
2.9%
6 2
 
2.9%
9 1
 
1.5%
Other Punctuation
ValueCountFrequency (%)
: 8
66.7%
. 4
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2833452
> 99.9%
Common 96
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 312625
 
11.0%
o 247355
 
8.7%
i 219282
 
7.7%
s 204987
 
7.2%
e 199721
 
7.0%
r 183312
 
6.5%
t 142209
 
5.0%
l 138064
 
4.9%
n 131110
 
4.6%
u 127288
 
4.5%
Other values (42) 927499
32.7%
Common
ValueCountFrequency (%)
2 18
18.8%
- 16
16.7%
1 16
16.7%
0 13
13.5%
: 8
8.3%
7 6
 
6.2%
4 4
 
4.2%
. 4
 
4.2%
3 3
 
3.1%
8 3
 
3.1%
Other values (3) 5
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2833548
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 312625
 
11.0%
o 247355
 
8.7%
i 219282
 
7.7%
s 204987
 
7.2%
e 199721
 
7.0%
r 183312
 
6.5%
t 142209
 
5.0%
l 138064
 
4.9%
n 131110
 
4.6%
u 127288
 
4.5%
Other values (55) 927595
32.7%

genericName
Text

Missing 

Distinct19280
Distinct (%)6.3%
Missing34393
Missing (%)10.2%
Memory size2.6 MiB
2025-01-08T17:43:03.969819image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length19
Mean length9.355540482
Min length3

Characters and Unicode

Total characters2841287
Distinct characters60
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2065 ?
Unique (%)0.7%

Sample

1st rowRectiostoma
2nd rowPolystichum
3rd rowMesontoplatys
4th rowBursa
5th rowAmanses
ValueCountFrequency (%)
plethodon 4671
 
1.5%
orconectes 4548
 
1.5%
procambarus 3716
 
1.2%
bathymodiolus 2598
 
0.9%
riftia 2006
 
0.7%
tursiops 1919
 
0.6%
cambarus 1853
 
0.6%
delphinus 1662
 
0.5%
aegla 1424
 
0.5%
anolis 1388
 
0.5%
Other values (19270) 277916
91.5%
2025-01-08T17:43:04.222420image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 309944
 
10.9%
o 245779
 
8.7%
i 214451
 
7.5%
e 208150
 
7.3%
s 204498
 
7.2%
r 186229
 
6.6%
t 147357
 
5.2%
l 138695
 
4.9%
n 130165
 
4.6%
u 122278
 
4.3%
Other values (50) 933741
32.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2537482
89.3%
Uppercase Letter 303711
 
10.7%
Decimal Number 68
 
< 0.1%
Dash Punctuation 14
 
< 0.1%
Other Punctuation 12
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 309944
12.2%
o 245779
 
9.7%
i 214451
 
8.5%
e 208150
 
8.2%
s 204498
 
8.1%
r 186229
 
7.3%
t 147357
 
5.8%
l 138695
 
5.5%
n 130165
 
5.1%
u 122278
 
4.8%
Other values (16) 629936
24.8%
Uppercase Letter
ValueCountFrequency (%)
P 47262
15.6%
C 36122
11.9%
A 32888
10.8%
S 23249
 
7.7%
M 18480
 
6.1%
E 17680
 
5.8%
L 16185
 
5.3%
H 15736
 
5.2%
T 13906
 
4.6%
D 13383
 
4.4%
Other values (16) 68820
22.7%
Decimal Number
ValueCountFrequency (%)
1 28
41.2%
2 16
23.5%
0 12
17.6%
7 8
 
11.8%
4 4
 
5.9%
Other Punctuation
ValueCountFrequency (%)
: 8
66.7%
. 4
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2841193
> 99.9%
Common 94
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 309944
 
10.9%
o 245779
 
8.7%
i 214451
 
7.5%
e 208150
 
7.3%
s 204498
 
7.2%
r 186229
 
6.6%
t 147357
 
5.2%
l 138695
 
4.9%
n 130165
 
4.6%
u 122278
 
4.3%
Other values (42) 933647
32.9%
Common
ValueCountFrequency (%)
1 28
29.8%
2 16
17.0%
- 14
14.9%
0 12
12.8%
: 8
 
8.5%
7 8
 
8.5%
4 4
 
4.3%
. 4
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2841287
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 309944
 
10.9%
o 245779
 
8.7%
i 214451
 
7.5%
e 208150
 
7.3%
s 204498
 
7.2%
r 186229
 
6.6%
t 147357
 
5.2%
l 138695
 
4.9%
n 130165
 
4.6%
u 122278
 
4.3%
Other values (50) 933741
32.9%

subgenus
Text

Constant  Missing 

Distinct1
Distinct (%)25.0%
Missing338090
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:43:04.271966image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters16
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowtrue
2nd rowtrue
3rd rowtrue
4th rowtrue
ValueCountFrequency (%)
true 4
100.0%
2025-01-08T17:43:04.355802image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 4
25.0%
r 4
25.0%
u 4
25.0%
e 4
25.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 16
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 4
25.0%
r 4
25.0%
u 4
25.0%
e 4
25.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 16
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 4
25.0%
r 4
25.0%
u 4
25.0%
e 4
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 4
25.0%
r 4
25.0%
u 4
25.0%
e 4
25.0%

specificEpithet
Text

Missing 

Distinct22410
Distinct (%)9.0%
Missing89523
Missing (%)26.5%
Memory size2.6 MiB
2025-01-08T17:43:04.544626image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length18
Mean length8.891676825
Min length2

Characters and Unicode

Total characters2210213
Distinct characters28
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3280 ?
Unique (%)1.3%

Sample

1st rowfernaldella
2nd rowbolzi
3rd rowgranularis
4th rowscopas
5th rowextenta
ValueCountFrequency (%)
truncatus 1929
 
0.8%
cinereus 1842
 
0.7%
delphis 1660
 
0.7%
porphyriticus 815
 
0.3%
acutus 778
 
0.3%
opacum 765
 
0.3%
hoffmani 639
 
0.3%
maculatus 632
 
0.3%
nigripes 624
 
0.3%
carolinensis 597
 
0.2%
Other values (22400) 238290
95.9%
2025-01-08T17:43:04.807997image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 289852
13.1%
i 243869
11.0%
s 189586
 
8.6%
e 172279
 
7.8%
r 150335
 
6.8%
l 148609
 
6.7%
u 138502
 
6.3%
n 137838
 
6.2%
t 126139
 
5.7%
o 112282
 
5.1%
Other values (18) 500922
22.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2210057
> 99.9%
Dash Punctuation 156
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 289852
13.1%
i 243869
11.0%
s 189586
 
8.6%
e 172279
 
7.8%
r 150335
 
6.8%
l 148609
 
6.7%
u 138502
 
6.3%
n 137838
 
6.2%
t 126139
 
5.7%
o 112282
 
5.1%
Other values (17) 500766
22.7%
Dash Punctuation
ValueCountFrequency (%)
- 156
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2210057
> 99.9%
Common 156
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 289852
13.1%
i 243869
11.0%
s 189586
 
8.6%
e 172279
 
7.8%
r 150335
 
6.8%
l 148609
 
6.7%
u 138502
 
6.3%
n 137838
 
6.2%
t 126139
 
5.7%
o 112282
 
5.1%
Other values (17) 500766
22.7%
Common
ValueCountFrequency (%)
- 156
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2210212
> 99.9%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 289852
13.1%
i 243869
11.0%
s 189586
 
8.6%
e 172279
 
7.8%
r 150335
 
6.8%
l 148609
 
6.7%
u 138502
 
6.3%
n 137838
 
6.2%
t 126139
 
5.7%
o 112282
 
5.1%
Other values (17) 500921
22.7%
None
ValueCountFrequency (%)
ü 1
100.0%

infraspecificEpithet
Text

Missing 

Distinct1598
Distinct (%)17.6%
Missing328999
Missing (%)97.3%
Memory size2.6 MiB
2025-01-08T17:43:04.994151image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length14
Mean length9.015063222
Min length3

Characters and Unicode

Total characters81992
Distinct characters27
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique647 ?
Unique (%)7.1%

Sample

1st rowcinereus
2nd rowbenjamina
3rd rowmexicana
4th rowdoliatus
5th rowpallidirostris
ValueCountFrequency (%)
pennsylvanicus 615
 
6.8%
cinereus 494
 
5.4%
talpoides 246
 
2.7%
melas 245
 
2.7%
dickeyi 167
 
1.8%
meeki 106
 
1.2%
porteri 91
 
1.0%
fumeus 88
 
1.0%
parva 74
 
0.8%
couguar 61
 
0.7%
Other values (1588) 6908
76.0%
2025-01-08T17:43:05.238818image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 9129
11.1%
a 8963
10.9%
s 8483
10.3%
e 7210
 
8.8%
n 6911
 
8.4%
u 5147
 
6.3%
r 5031
 
6.1%
l 4672
 
5.7%
c 4450
 
5.4%
o 3740
 
4.6%
Other values (17) 18256
22.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 81989
> 99.9%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 9129
11.1%
a 8963
10.9%
s 8483
10.3%
e 7210
 
8.8%
n 6911
 
8.4%
u 5147
 
6.3%
r 5031
 
6.1%
l 4672
 
5.7%
c 4450
 
5.4%
o 3740
 
4.6%
Other values (16) 18253
22.3%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 81989
> 99.9%
Common 3
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 9129
11.1%
a 8963
10.9%
s 8483
10.3%
e 7210
 
8.8%
n 6911
 
8.4%
u 5147
 
6.3%
r 5031
 
6.1%
l 4672
 
5.7%
c 4450
 
5.4%
o 3740
 
4.6%
Other values (16) 18253
22.3%
Common
ValueCountFrequency (%)
- 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 81992
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 9129
11.1%
a 8963
10.9%
s 8483
10.3%
e 7210
 
8.8%
n 6911
 
8.4%
u 5147
 
6.3%
r 5031
 
6.1%
l 4672
 
5.7%
c 4450
 
5.4%
o 3740
 
4.6%
Other values (17) 18256
22.3%

cultivarEpithet
Text

Missing 

Distinct3
Distinct (%)75.0%
Missing338090
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:43:05.296861image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length10
Mean length9.25
Min length4

Characters and Unicode

Total characters37
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st rowASIA
2nd rowLATIN_AMERICA
3rd rowOCEANIA
4th rowLATIN_AMERICA
ValueCountFrequency (%)
latin_america 2
50.0%
asia 1
25.0%
oceania 1
25.0%
2025-01-08T17:43:05.388211image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 10
27.0%
I 6
16.2%
N 3
 
8.1%
E 3
 
8.1%
C 3
 
8.1%
L 2
 
5.4%
T 2
 
5.4%
_ 2
 
5.4%
M 2
 
5.4%
R 2
 
5.4%
Other values (2) 2
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 35
94.6%
Connector Punctuation 2
 
5.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 10
28.6%
I 6
17.1%
N 3
 
8.6%
E 3
 
8.6%
C 3
 
8.6%
L 2
 
5.7%
T 2
 
5.7%
M 2
 
5.7%
R 2
 
5.7%
S 1
 
2.9%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 35
94.6%
Common 2
 
5.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 10
28.6%
I 6
17.1%
N 3
 
8.6%
E 3
 
8.6%
C 3
 
8.6%
L 2
 
5.7%
T 2
 
5.7%
M 2
 
5.7%
R 2
 
5.7%
S 1
 
2.9%
Common
ValueCountFrequency (%)
_ 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 10
27.0%
I 6
16.2%
N 3
 
8.1%
E 3
 
8.1%
C 3
 
8.1%
L 2
 
5.4%
T 2
 
5.4%
_ 2
 
5.4%
M 2
 
5.4%
R 2
 
5.4%
Other values (2) 2
 
5.4%
Distinct11
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Memory size2.6 MiB
2025-01-08T17:43:05.432573image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length7
Mean length6.638623101
Min length4

Characters and Unicode

Total characters2244472
Distinct characters22
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSPECIES
2nd rowFAMILY
3rd rowFAMILY
4th rowFAMILY
5th rowGENUS
ValueCountFrequency (%)
species 239484
70.8%
genus 55123
 
16.3%
family 14870
 
4.4%
subspecies 8236
 
2.4%
kingdom 6690
 
2.0%
order 4994
 
1.5%
phylum 4014
 
1.2%
class 3823
 
1.1%
variety 806
 
0.2%
form 49
 
< 0.1%
2025-01-08T17:43:05.539005image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 566445
25.2%
E 556367
24.8%
I 270090
12.0%
P 251734
11.2%
C 251547
11.2%
U 67373
 
3.0%
N 61817
 
2.8%
G 61813
 
2.8%
M 25627
 
1.1%
L 22707
 
1.0%
Other values (12) 108952
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2244468
> 99.9%
Connector Punctuation 4
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 566445
25.2%
E 556367
24.8%
I 270090
12.0%
P 251734
11.2%
C 251547
11.2%
U 67373
 
3.0%
N 61817
 
2.8%
G 61813
 
2.8%
M 25627
 
1.1%
L 22707
 
1.0%
Other values (11) 108948
 
4.9%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2244468
> 99.9%
Common 4
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 566445
25.2%
E 556367
24.8%
I 270090
12.0%
P 251734
11.2%
C 251547
11.2%
U 67373
 
3.0%
N 61817
 
2.8%
G 61813
 
2.8%
M 25627
 
1.1%
L 22707
 
1.0%
Other values (11) 108948
 
4.9%
Common
ValueCountFrequency (%)
_ 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2244472
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 566445
25.2%
E 556367
24.8%
I 270090
12.0%
P 251734
11.2%
C 251547
11.2%
U 67373
 
3.0%
N 61817
 
2.8%
G 61813
 
2.8%
M 25627
 
1.1%
L 22707
 
1.0%
Other values (12) 108952
 
4.9%

verbatimTaxonRank
Text

Missing 

Distinct3
Distinct (%)75.0%
Missing338090
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:43:05.582277image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters12
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st rowPHL
2nd rowGUY
3rd rowPLW
4th rowGUY
ValueCountFrequency (%)
guy 2
50.0%
phl 1
25.0%
plw 1
25.0%
2025-01-08T17:43:05.784712image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
G 2
16.7%
U 2
16.7%
Y 2
16.7%
P 2
16.7%
L 2
16.7%
H 1
8.3%
W 1
8.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 12
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
G 2
16.7%
U 2
16.7%
Y 2
16.7%
P 2
16.7%
L 2
16.7%
H 1
8.3%
W 1
8.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 12
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
G 2
16.7%
U 2
16.7%
Y 2
16.7%
P 2
16.7%
L 2
16.7%
H 1
8.3%
W 1
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
G 2
16.7%
U 2
16.7%
Y 2
16.7%
P 2
16.7%
L 2
16.7%
H 1
8.3%
W 1
8.3%

vernacularName
Text

Missing 

Distinct3
Distinct (%)75.0%
Missing338090
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:43:05.824713image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length11
Median length8.5
Mean length7
Min length5

Characters and Unicode

Total characters28
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st rowPhilippines
2nd rowGuyana
3rd rowPalau
4th rowGuyana
ValueCountFrequency (%)
guyana 2
50.0%
philippines 1
25.0%
palau 1
25.0%
2025-01-08T17:43:05.920939image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 6
21.4%
u 3
10.7%
n 3
10.7%
i 3
10.7%
G 2
 
7.1%
y 2
 
7.1%
P 2
 
7.1%
l 2
 
7.1%
p 2
 
7.1%
h 1
 
3.6%
Other values (2) 2
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 24
85.7%
Uppercase Letter 4
 
14.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 6
25.0%
u 3
12.5%
n 3
12.5%
i 3
12.5%
y 2
 
8.3%
l 2
 
8.3%
p 2
 
8.3%
h 1
 
4.2%
e 1
 
4.2%
s 1
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
G 2
50.0%
P 2
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 28
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 6
21.4%
u 3
10.7%
n 3
10.7%
i 3
10.7%
G 2
 
7.1%
y 2
 
7.1%
P 2
 
7.1%
l 2
 
7.1%
p 2
 
7.1%
h 1
 
3.6%
Other values (2) 2
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 6
21.4%
u 3
10.7%
n 3
10.7%
i 3
10.7%
G 2
 
7.1%
y 2
 
7.1%
P 2
 
7.1%
l 2
 
7.1%
p 2
 
7.1%
h 1
 
3.6%
Other values (2) 2
 
7.1%

nomenclaturalCode
Text

Missing 

Distinct3
Distinct (%)75.0%
Missing338090
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:43:05.962387image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length7
Mean length7.25
Min length7

Characters and Unicode

Total characters29
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st rowPHL.36_1
2nd rowGUY.2_1
3rd rowPLW.6_1
4th rowGUY.2_1
ValueCountFrequency (%)
guy.2_1 2
50.0%
phl.36_1 1
25.0%
plw.6_1 1
25.0%
2025-01-08T17:43:06.059448image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 4
13.8%
_ 4
13.8%
1 4
13.8%
G 2
6.9%
U 2
6.9%
Y 2
6.9%
2 2
6.9%
P 2
6.9%
L 2
6.9%
6 2
6.9%
Other values (3) 3
10.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 12
41.4%
Decimal Number 9
31.0%
Other Punctuation 4
 
13.8%
Connector Punctuation 4
 
13.8%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
G 2
16.7%
U 2
16.7%
Y 2
16.7%
P 2
16.7%
L 2
16.7%
H 1
8.3%
W 1
8.3%
Decimal Number
ValueCountFrequency (%)
1 4
44.4%
2 2
22.2%
6 2
22.2%
3 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17
58.6%
Latin 12
41.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
G 2
16.7%
U 2
16.7%
Y 2
16.7%
P 2
16.7%
L 2
16.7%
H 1
8.3%
W 1
8.3%
Common
ValueCountFrequency (%)
. 4
23.5%
_ 4
23.5%
1 4
23.5%
2 2
11.8%
6 2
11.8%
3 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 4
13.8%
_ 4
13.8%
1 4
13.8%
G 2
6.9%
U 2
6.9%
Y 2
6.9%
2 2
6.9%
P 2
6.9%
L 2
6.9%
6 2
6.9%
Other values (3) 3
10.3%

taxonomicStatus
Text

Missing 

Distinct6
Distinct (%)< 0.1%
Missing6108
Missing (%)1.8%
Memory size2.6 MiB
2025-01-08T17:43:06.104162image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length15
Median length8
Mean length7.926999934
Min length5

Characters and Unicode

Total characters2631653
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowACCEPTED
2nd rowACCEPTED
3rd rowACCEPTED
4th rowACCEPTED
5th rowACCEPTED
ValueCountFrequency (%)
accepted 305150
91.9%
synonym 24244
 
7.3%
doubtful 2588
 
0.8%
cuyuni-mazaruni 2
 
< 0.1%
iloilo 1
 
< 0.1%
koror 1
 
< 0.1%
2025-01-08T17:43:06.199767image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 610302
23.2%
E 610300
23.2%
T 307738
11.7%
D 307738
11.7%
A 305150
11.6%
P 305150
11.6%
Y 48488
 
1.8%
N 48488
 
1.8%
O 26832
 
1.0%
M 24246
 
0.9%
Other values (17) 37221
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2631618
> 99.9%
Lowercase Letter 33
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 610302
23.2%
E 610300
23.2%
T 307738
11.7%
D 307738
11.7%
A 305150
11.6%
P 305150
11.6%
Y 48488
 
1.8%
N 48488
 
1.8%
O 26832
 
1.0%
M 24246
 
0.9%
Other values (7) 37186
 
1.4%
Lowercase Letter
ValueCountFrequency (%)
u 6
18.2%
i 5
15.2%
n 4
12.1%
a 4
12.1%
r 4
12.1%
o 4
12.1%
y 2
 
6.1%
z 2
 
6.1%
l 2
 
6.1%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2631651
> 99.9%
Common 2
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 610302
23.2%
E 610300
23.2%
T 307738
11.7%
D 307738
11.7%
A 305150
11.6%
P 305150
11.6%
Y 48488
 
1.8%
N 48488
 
1.8%
O 26832
 
1.0%
M 24246
 
0.9%
Other values (16) 37219
 
1.4%
Common
ValueCountFrequency (%)
- 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2631653
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
C 610302
23.2%
E 610300
23.2%
T 307738
11.7%
D 307738
11.7%
A 305150
11.6%
P 305150
11.6%
Y 48488
 
1.8%
N 48488
 
1.8%
O 26832
 
1.0%
M 24246
 
0.9%
Other values (17) 37221
 
1.4%

nomenclaturalStatus
Text

Missing 

Distinct2
Distinct (%)66.7%
Missing338091
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:43:06.243499image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length11
Median length9
Mean length9.666666667
Min length9

Characters and Unicode

Total characters29
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st rowPHL.36.21_1
2nd rowGUY.2.8_1
3rd rowGUY.2.8_1
ValueCountFrequency (%)
guy.2.8_1 2
66.7%
phl.36.21_1 1
33.3%
2025-01-08T17:43:06.341715image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 6
20.7%
1 4
13.8%
2 3
10.3%
_ 3
10.3%
G 2
 
6.9%
U 2
 
6.9%
Y 2
 
6.9%
8 2
 
6.9%
P 1
 
3.4%
H 1
 
3.4%
Other values (3) 3
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11
37.9%
Uppercase Letter 9
31.0%
Other Punctuation 6
20.7%
Connector Punctuation 3
 
10.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
G 2
22.2%
U 2
22.2%
Y 2
22.2%
P 1
11.1%
H 1
11.1%
L 1
11.1%
Decimal Number
ValueCountFrequency (%)
1 4
36.4%
2 3
27.3%
8 2
18.2%
3 1
 
9.1%
6 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
. 6
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20
69.0%
Latin 9
31.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 6
30.0%
1 4
20.0%
2 3
15.0%
_ 3
15.0%
8 2
 
10.0%
3 1
 
5.0%
6 1
 
5.0%
Latin
ValueCountFrequency (%)
G 2
22.2%
U 2
22.2%
Y 2
22.2%
P 1
11.1%
H 1
11.1%
L 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 6
20.7%
1 4
13.8%
2 3
10.3%
_ 3
10.3%
G 2
 
6.9%
U 2
 
6.9%
Y 2
 
6.9%
8 2
 
6.9%
P 1
 
3.4%
H 1
 
3.4%
Other values (3) 3
10.3%

taxonRemarks
Text

Missing 

Distinct2
Distinct (%)66.7%
Missing338091
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:43:06.383715image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length16
Median length16
Mean length14.33333333
Min length11

Characters and Unicode

Total characters43
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st rowIloilo City
2nd rowRest of Region 7
3rd rowRest of Region 7
ValueCountFrequency (%)
rest 2
20.0%
of 2
20.0%
region 2
20.0%
7 2
20.0%
iloilo 1
10.0%
city 1
10.0%
2025-01-08T17:43:06.478906image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
16.3%
o 6
14.0%
R 4
9.3%
e 4
9.3%
i 4
9.3%
t 3
7.0%
s 2
 
4.7%
f 2
 
4.7%
g 2
 
4.7%
n 2
 
4.7%
Other values (5) 7
16.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 28
65.1%
Space Separator 7
 
16.3%
Uppercase Letter 6
 
14.0%
Decimal Number 2
 
4.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 6
21.4%
e 4
14.3%
i 4
14.3%
t 3
10.7%
s 2
 
7.1%
f 2
 
7.1%
g 2
 
7.1%
n 2
 
7.1%
l 2
 
7.1%
y 1
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
R 4
66.7%
I 1
 
16.7%
C 1
 
16.7%
Space Separator
ValueCountFrequency (%)
7
100.0%
Decimal Number
ValueCountFrequency (%)
7 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 34
79.1%
Common 9
 
20.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 6
17.6%
R 4
11.8%
e 4
11.8%
i 4
11.8%
t 3
8.8%
s 2
 
5.9%
f 2
 
5.9%
g 2
 
5.9%
n 2
 
5.9%
l 2
 
5.9%
Other values (3) 3
8.8%
Common
ValueCountFrequency (%)
7
77.8%
7 2
 
22.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
16.3%
o 6
14.0%
R 4
9.3%
e 4
9.3%
i 4
9.3%
t 3
7.0%
s 2
 
4.7%
f 2
 
4.7%
g 2
 
4.7%
n 2
 
4.7%
Other values (5) 7
16.3%
Distinct2
Distinct (%)< 0.1%
Missing4
Missing (%)< 0.1%
Memory size2.6 MiB
2025-01-08T17:43:06.533345image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length36
Median length36
Mean length35.99993493
Min length14

Characters and Unicode

Total characters12171218
Distinct characters22
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row26098c25-8f7f-4c71-97ac-1d3db181c65e
2nd row26098c25-8f7f-4c71-97ac-1d3db181c65e
3rd row26098c25-8f7f-4c71-97ac-1d3db181c65e
4th row26098c25-8f7f-4c71-97ac-1d3db181c65e
5th row26098c25-8f7f-4c71-97ac-1d3db181c65e
ValueCountFrequency (%)
26098c25-8f7f-4c71-97ac-1d3db181c65e 338089
> 99.9%
phl.36.21.66_1 1
 
< 0.1%
2025-01-08T17:43:06.635697image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1352358
11.1%
- 1352356
11.1%
c 1352356
11.1%
7 1014267
 
8.3%
8 1014267
 
8.3%
6 676181
 
5.6%
2 676179
 
5.6%
5 676178
 
5.6%
f 676178
 
5.6%
9 676178
 
5.6%
Other values (12) 2704720
22.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7099876
58.3%
Lowercase Letter 3718979
30.6%
Dash Punctuation 1352356
 
11.1%
Other Punctuation 3
 
< 0.1%
Uppercase Letter 3
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1352358
19.0%
7 1014267
14.3%
8 1014267
14.3%
6 676181
9.5%
2 676179
9.5%
5 676178
9.5%
9 676178
9.5%
3 338090
 
4.8%
4 338089
 
4.8%
0 338089
 
4.8%
Lowercase Letter
ValueCountFrequency (%)
c 1352356
36.4%
f 676178
18.2%
d 676178
18.2%
a 338089
 
9.1%
b 338089
 
9.1%
e 338089
 
9.1%
Uppercase Letter
ValueCountFrequency (%)
P 1
33.3%
H 1
33.3%
L 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1352356
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8452236
69.4%
Latin 3718982
30.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1352358
16.0%
- 1352356
16.0%
7 1014267
12.0%
8 1014267
12.0%
6 676181
8.0%
2 676179
8.0%
5 676178
8.0%
9 676178
8.0%
3 338090
 
4.0%
4 338089
 
4.0%
Other values (3) 338093
 
4.0%
Latin
ValueCountFrequency (%)
c 1352356
36.4%
f 676178
18.2%
d 676178
18.2%
a 338089
 
9.1%
b 338089
 
9.1%
e 338089
 
9.1%
P 1
 
< 0.1%
H 1
 
< 0.1%
L 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12171218
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1352358
11.1%
- 1352356
11.1%
c 1352356
11.1%
7 1014267
 
8.3%
8 1014267
 
8.3%
6 676181
 
5.6%
2 676179
 
5.6%
5 676178
 
5.6%
f 676178
 
5.6%
9 676178
 
5.6%
Other values (12) 2704720
22.2%
Distinct2
Distinct (%)< 0.1%
Missing4
Missing (%)< 0.1%
Memory size2.6 MiB
2025-01-08T17:43:06.675698image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length2
Mean length2.000020705
Min length2

Characters and Unicode

Total characters676187
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowUS
2nd rowUS
3rd rowUS
4th rowUS
5th rowUS
ValueCountFrequency (%)
us 338089
> 99.9%
kahirupan 1
 
< 0.1%
2025-01-08T17:43:06.773877image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 338089
50.0%
S 338089
50.0%
a 2
 
< 0.1%
K 1
 
< 0.1%
h 1
 
< 0.1%
i 1
 
< 0.1%
r 1
 
< 0.1%
u 1
 
< 0.1%
p 1
 
< 0.1%
n 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 676179
> 99.9%
Lowercase Letter 8
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 2
25.0%
h 1
12.5%
i 1
12.5%
r 1
12.5%
u 1
12.5%
p 1
12.5%
n 1
12.5%
Uppercase Letter
ValueCountFrequency (%)
U 338089
50.0%
S 338089
50.0%
K 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 676187
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U 338089
50.0%
S 338089
50.0%
a 2
 
< 0.1%
K 1
 
< 0.1%
h 1
 
< 0.1%
i 1
 
< 0.1%
r 1
 
< 0.1%
u 1
 
< 0.1%
p 1
 
< 0.1%
n 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 676187
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U 338089
50.0%
S 338089
50.0%
a 2
 
< 0.1%
K 1
 
< 0.1%
h 1
 
< 0.1%
i 1
 
< 0.1%
r 1
 
< 0.1%
u 1
 
< 0.1%
p 1
 
< 0.1%
n 1
 
< 0.1%
Distinct31889
Distinct (%)9.4%
Missing1
Missing (%)< 0.1%
Memory size2.6 MiB
2025-01-08T17:43:06.874023image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length24
Mean length23.9958118
Min length2

Characters and Unicode

Total characters8112816
Distinct characters19
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3501 ?
Unique (%)1.0%

Sample

1st row2024-12-01T12:07:01.240Z
2nd row2024-12-01T12:07:01.438Z
3rd row2024-12-01T12:07:01.443Z
4th row2024-12-01T12:07:01.449Z
5th row2024-12-01T12:07:01.465Z
ValueCountFrequency (%)
2024-12-01t12:07:38.532z 73
 
< 0.1%
2024-12-01t12:07:38.533z 71
 
< 0.1%
2024-12-01t12:07:38.508z 68
 
< 0.1%
2024-12-01t12:07:39.879z 67
 
< 0.1%
2024-12-01t12:07:37.936z 65
 
< 0.1%
2024-12-01t12:07:40.339z 65
 
< 0.1%
2024-12-01t12:07:39.819z 65
 
< 0.1%
2024-12-01t12:07:39.723z 64
 
< 0.1%
2024-12-01t12:07:39.875z 64
 
< 0.1%
2024-12-01t12:07:38.854z 63
 
< 0.1%
Other values (31879) 337428
99.8%
2025-01-08T17:43:07.035071image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1562001
19.3%
1 1172147
14.4%
0 1166550
14.4%
- 676178
8.3%
: 676178
8.3%
4 503489
 
6.2%
7 475460
 
5.9%
Z 338089
 
4.2%
T 338089
 
4.2%
. 337757
 
4.2%
Other values (9) 866878
10.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5746517
70.8%
Other Punctuation 1013935
 
12.5%
Uppercase Letter 676186
 
8.3%
Dash Punctuation 676178
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1562001
27.2%
1 1172147
20.4%
0 1166550
20.3%
4 503489
 
8.8%
7 475460
 
8.3%
3 314692
 
5.5%
8 145833
 
2.5%
9 145808
 
2.5%
6 137824
 
2.4%
5 122713
 
2.1%
Uppercase Letter
ValueCountFrequency (%)
Z 338089
50.0%
T 338089
50.0%
N 3
 
< 0.1%
E 3
 
< 0.1%
L 1
 
< 0.1%
C 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
: 676178
66.7%
. 337757
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 676178
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7436630
91.7%
Latin 676186
 
8.3%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1562001
21.0%
1 1172147
15.8%
0 1166550
15.7%
- 676178
9.1%
: 676178
9.1%
4 503489
 
6.8%
7 475460
 
6.4%
. 337757
 
4.5%
3 314692
 
4.2%
8 145833
 
2.0%
Other values (3) 406345
 
5.5%
Latin
ValueCountFrequency (%)
Z 338089
50.0%
T 338089
50.0%
N 3
 
< 0.1%
E 3
 
< 0.1%
L 1
 
< 0.1%
C 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8112816
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1562001
19.3%
1 1172147
14.4%
0 1166550
14.4%
- 676178
8.3%
: 676178
8.3%
4 503489
 
6.2%
7 475460
 
5.9%
Z 338089
 
4.2%
T 338089
 
4.2%
. 337757
 
4.2%
Other values (9) 866878
10.7%

elevation
Text

Missing 

Distinct2734
Distinct (%)3.1%
Missing248950
Missing (%)73.6%
Memory size2.6 MiB
2025-01-08T17:43:07.225426image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.182614646
Min length3

Characters and Unicode

Total characters461999
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique260 ?
Unique (%)0.3%

Sample

1st row1524.0
2nd row2700.0
3rd row1800.0
4th row1000.0
5th row760.0
ValueCountFrequency (%)
5.0 1545
 
1.7%
1100.0 1195
 
1.3%
1200.0 995
 
1.1%
150.0 967
 
1.1%
200.0 779
 
0.9%
1829.0 757
 
0.8%
50.0 700
 
0.8%
300.0 694
 
0.8%
1487.0 632
 
0.7%
100.0 612
 
0.7%
Other values (2721) 80268
90.0%
2025-01-08T17:43:07.489183image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 137608
29.8%
. 89144
19.3%
1 52547
 
11.4%
2 36028
 
7.8%
5 32914
 
7.1%
3 23010
 
5.0%
4 21188
 
4.6%
7 19318
 
4.2%
6 17558
 
3.8%
8 17037
 
3.7%
Other values (2) 15647
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 372843
80.7%
Other Punctuation 89144
 
19.3%
Dash Punctuation 12
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 137608
36.9%
1 52547
 
14.1%
2 36028
 
9.7%
5 32914
 
8.8%
3 23010
 
6.2%
4 21188
 
5.7%
7 19318
 
5.2%
6 17558
 
4.7%
8 17037
 
4.6%
9 15635
 
4.2%
Other Punctuation
ValueCountFrequency (%)
. 89144
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 461999
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 137608
29.8%
. 89144
19.3%
1 52547
 
11.4%
2 36028
 
7.8%
5 32914
 
7.1%
3 23010
 
5.0%
4 21188
 
4.6%
7 19318
 
4.2%
6 17558
 
3.8%
8 17037
 
3.7%
Other values (2) 15647
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 461999
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 137608
29.8%
. 89144
19.3%
1 52547
 
11.4%
2 36028
 
7.8%
5 32914
 
7.1%
3 23010
 
5.0%
4 21188
 
4.6%
7 19318
 
4.2%
6 17558
 
3.8%
8 17037
 
3.7%
Other values (2) 15647
 
3.4%

elevationAccuracy
Text

Missing 

Distinct161
Distinct (%)0.3%
Missing284393
Missing (%)84.1%
Memory size2.6 MiB
2025-01-08T17:43:07.628928image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.090705946
Min length3

Characters and Unicode

Total characters165974
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0 47745
88.9%
2.5 1013
 
1.9%
25.0 410
 
0.8%
100.0 392
 
0.7%
1.0 356
 
0.7%
5.0 307
 
0.6%
12.5 218
 
0.4%
50.0 212
 
0.4%
38.75 206
 
0.4%
30.5 167
 
0.3%
Other values (151) 2675
 
5.0%
2025-01-08T17:43:07.813133image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 100330
60.4%
. 53701
32.4%
5 4596
 
2.8%
2 2430
 
1.5%
1 2117
 
1.3%
7 818
 
0.5%
3 727
 
0.4%
8 446
 
0.3%
4 336
 
0.2%
9 237
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 112273
67.6%
Other Punctuation 53701
32.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 100330
89.4%
5 4596
 
4.1%
2 2430
 
2.2%
1 2117
 
1.9%
7 818
 
0.7%
3 727
 
0.6%
8 446
 
0.4%
4 336
 
0.3%
9 237
 
0.2%
6 236
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 53701
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 165974
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 100330
60.4%
. 53701
32.4%
5 4596
 
2.8%
2 2430
 
1.5%
1 2117
 
1.3%
7 818
 
0.5%
3 727
 
0.4%
8 446
 
0.3%
4 336
 
0.2%
9 237
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 165974
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 100330
60.4%
. 53701
32.4%
5 4596
 
2.8%
2 2430
 
1.5%
1 2117
 
1.3%
7 818
 
0.5%
3 727
 
0.4%
8 446
 
0.3%
4 336
 
0.2%
9 237
 
0.1%

depth
Text

Missing 

Distinct2253
Distinct (%)3.0%
Missing262666
Missing (%)77.7%
Memory size2.6 MiB
2025-01-08T17:43:07.992750image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length18
Mean length4.257742483
Min length3

Characters and Unicode

Total characters321153
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique642 ?
Unique (%)0.9%

Sample

1st row1785.34
2nd row15.0
3rd row49.0
4th row30.0
5th row3456.48
ValueCountFrequency (%)
0.5 5165
 
6.8%
3.0 4287
 
5.7%
1.5 4042
 
5.4%
1.0 3416
 
4.5%
2.0 1940
 
2.6%
10.0 1543
 
2.0%
15.0 1120
 
1.5%
0.0 937
 
1.2%
17.5 933
 
1.2%
2.5 888
 
1.2%
Other values (2243) 51157
67.8%
2025-01-08T17:43:08.230544image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 75428
23.5%
0 60955
19.0%
5 42952
13.4%
1 38545
12.0%
2 28079
 
8.7%
3 18294
 
5.7%
7 13595
 
4.2%
6 12603
 
3.9%
4 10944
 
3.4%
8 10252
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 245725
76.5%
Other Punctuation 75428
 
23.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 60955
24.8%
5 42952
17.5%
1 38545
15.7%
2 28079
11.4%
3 18294
 
7.4%
7 13595
 
5.5%
6 12603
 
5.1%
4 10944
 
4.5%
8 10252
 
4.2%
9 9506
 
3.9%
Other Punctuation
ValueCountFrequency (%)
. 75428
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 321153
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 75428
23.5%
0 60955
19.0%
5 42952
13.4%
1 38545
12.0%
2 28079
 
8.7%
3 18294
 
5.7%
7 13595
 
4.2%
6 12603
 
3.9%
4 10944
 
3.4%
8 10252
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 321153
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 75428
23.5%
0 60955
19.0%
5 42952
13.4%
1 38545
12.0%
2 28079
 
8.7%
3 18294
 
5.7%
7 13595
 
4.2%
6 12603
 
3.9%
4 10944
 
3.4%
8 10252
 
3.2%

depthAccuracy
Text

Missing 

Distinct239
Distinct (%)0.4%
Missing272182
Missing (%)80.5%
Memory size2.6 MiB
2025-01-08T17:43:08.404878image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length3
Mean length3.292753975
Min length3

Characters and Unicode

Total characters217032
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row2.0
3rd row49.0
4th row5.0
5th row0.0
ValueCountFrequency (%)
0.0 26153
39.7%
0.5 5488
 
8.3%
1.5 4808
 
7.3%
1.0 2977
 
4.5%
2.0 2346
 
3.6%
2.5 2341
 
3.6%
3.0 1911
 
2.9%
0.25 1393
 
2.1%
5.0 1251
 
1.9%
4.0 1139
 
1.7%
Other values (229) 16105
24.4%
2025-01-08T17:43:08.640507image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 81443
37.5%
. 65912
30.4%
5 27649
 
12.7%
1 12282
 
5.7%
2 8722
 
4.0%
3 4835
 
2.2%
4 4807
 
2.2%
7 4279
 
2.0%
9 3447
 
1.6%
6 2344
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 151120
69.6%
Other Punctuation 65912
30.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 81443
53.9%
5 27649
 
18.3%
1 12282
 
8.1%
2 8722
 
5.8%
3 4835
 
3.2%
4 4807
 
3.2%
7 4279
 
2.8%
9 3447
 
2.3%
6 2344
 
1.6%
8 1312
 
0.9%
Other Punctuation
ValueCountFrequency (%)
. 65912
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 217032
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 81443
37.5%
. 65912
30.4%
5 27649
 
12.7%
1 12282
 
5.7%
2 8722
 
4.0%
3 4835
 
2.2%
4 4807
 
2.2%
7 4279
 
2.0%
9 3447
 
1.6%
6 2344
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 217032
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 81443
37.5%
. 65912
30.4%
5 27649
 
12.7%
1 12282
 
5.7%
2 8722
 
4.0%
3 4835
 
2.2%
4 4807
 
2.2%
7 4279
 
2.0%
9 3447
 
1.6%
6 2344
 
1.1%
Distinct170
Distinct (%)6.3%
Missing335404
Missing (%)99.2%
Memory size2.6 MiB
2025-01-08T17:43:08.753714image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length17
Mean length17.28847584
Min length3

Characters and Unicode

Total characters46506
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)1.0%

Sample

1st row2259.882955420656
2nd row4272.023262908208
3rd row3797.0726080073355
4th row4837.263464897006
5th row1142.6033371248081
ValueCountFrequency (%)
3997.886559051776 239
 
8.9%
818.1211019658687 183
 
6.8%
918.1358064728217 159
 
5.9%
3435.2993691323722 143
 
5.3%
1914.9010623948639 138
 
5.1%
4049.579332802943 132
 
4.9%
3247.910831883673 94
 
3.5%
3286.3383926848273 91
 
3.4%
2259.882955420656 89
 
3.3%
3868.839758506256 70
 
2.6%
Other values (160) 1352
50.3%
2025-01-08T17:43:08.930927image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 5502
11.8%
8 5097
11.0%
2 4742
10.2%
9 4620
9.9%
1 4245
9.1%
6 4155
8.9%
7 4119
8.9%
5 3972
8.5%
4 3880
8.3%
0 3484
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 43816
94.2%
Other Punctuation 2690
 
5.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 5502
12.6%
8 5097
11.6%
2 4742
10.8%
9 4620
10.5%
1 4245
9.7%
6 4155
9.5%
7 4119
9.4%
5 3972
9.1%
4 3880
8.9%
0 3484
8.0%
Other Punctuation
ValueCountFrequency (%)
. 2690
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 46506
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 5502
11.8%
8 5097
11.0%
2 4742
10.2%
9 4620
9.9%
1 4245
9.1%
6 4155
8.9%
7 4119
8.9%
5 3972
8.5%
4 3880
8.3%
0 3484
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46506
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 5502
11.8%
8 5097
11.0%
2 4742
10.2%
9 4620
9.9%
1 4245
9.1%
6 4155
8.9%
7 4119
8.9%
5 3972
8.5%
4 3880
8.3%
0 3484
7.5%

issue
Text

Missing 

Distinct172
Distinct (%)0.1%
Missing45626
Missing (%)13.5%
Memory size2.6 MiB
2025-01-08T17:43:09.004927image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length197
Median length154
Mean length59.83685737
Min length15

Characters and Unicode

Total characters17500366
Distinct characters28
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)< 0.1%

Sample

1st rowGEODETIC_DATUM_ASSUMED_WGS84;CONTINENT_DERIVED_FROM_COORDINATES
2nd rowGEODETIC_DATUM_ASSUMED_WGS84;CONTINENT_INVALID
3rd rowGEODETIC_DATUM_ASSUMED_WGS84;CONTINENT_DERIVED_FROM_COORDINATES;CONTINENT_INVALID
4th rowGEODETIC_DATUM_ASSUMED_WGS84
5th rowGEODETIC_DATUM_ASSUMED_WGS84;CONTINENT_DERIVED_FROM_COORDINATES
ValueCountFrequency (%)
geodetic_datum_assumed_wgs84;continent_derived_from_coordinates 81966
28.0%
geodetic_datum_assumed_wgs84 50425
17.2%
geodetic_datum_assumed_wgs84;continent_derived_from_coordinates;continent_invalid 48259
16.5%
geodetic_datum_assumed_wgs84;continent_invalid 23627
 
8.1%
continent_derived_from_country 13936
 
4.8%
geodetic_datum_assumed_wgs84;geodetic_datum_invalid;continent_derived_from_coordinates;continent_invalid 12417
 
4.2%
geodetic_datum_assumed_wgs84;continent_derived_from_coordinates;taxon_match_higherrank 10213
 
3.5%
continent_derived_from_country;continent_invalid 6285
 
2.1%
geodetic_datum_assumed_wgs84;geodetic_datum_invalid;continent_derived_from_coordinates 4317
 
1.5%
country_derived_from_coordinates;geodetic_datum_assumed_wgs84;continent_invalid 3977
 
1.4%
Other values (162) 37046
12.7%
2025-01-08T17:43:09.139934image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 1740521
 
9.9%
_ 1614935
 
9.2%
D 1532749
 
8.8%
T 1465021
 
8.4%
N 1338780
 
7.7%
I 1261875
 
7.2%
O 1227170
 
7.0%
S 956544
 
5.5%
A 942202
 
5.4%
C 851797
 
4.9%
Other values (18) 4568772
26.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 15039613
85.9%
Connector Punctuation 1614935
 
9.2%
Decimal Number 509914
 
2.9%
Other Punctuation 335904
 
1.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 1740521
11.6%
D 1532749
10.2%
T 1465021
9.7%
N 1338780
8.9%
I 1261875
8.4%
O 1227170
8.2%
S 956544
 
6.4%
A 942202
 
6.3%
C 851797
 
5.7%
M 778930
 
5.2%
Other values (14) 2944024
19.6%
Decimal Number
ValueCountFrequency (%)
4 254957
50.0%
8 254957
50.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1614935
100.0%
Other Punctuation
ValueCountFrequency (%)
; 335904
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 15039613
85.9%
Common 2460753
 
14.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 1740521
11.6%
D 1532749
10.2%
T 1465021
9.7%
N 1338780
8.9%
I 1261875
8.4%
O 1227170
8.2%
S 956544
 
6.4%
A 942202
 
6.3%
C 851797
 
5.7%
M 778930
 
5.2%
Other values (14) 2944024
19.6%
Common
ValueCountFrequency (%)
_ 1614935
65.6%
; 335904
 
13.7%
4 254957
 
10.4%
8 254957
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17500366
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 1740521
 
9.9%
_ 1614935
 
9.2%
D 1532749
 
8.8%
T 1465021
 
8.4%
N 1338780
 
7.7%
I 1261875
 
7.2%
O 1227170
 
7.0%
S 956544
 
5.5%
A 942202
 
5.4%
C 851797
 
4.9%
Other values (18) 4568772
26.1%

mediaType
Text

Missing 

Distinct19
Distinct (%)0.1%
Missing324090
Missing (%)95.9%
Memory size2.6 MiB
2025-01-08T17:43:09.192670image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length362
Median length10
Mean length13.91095401
Min length10

Characters and Unicode

Total characters194809
Distinct characters10
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowStillImage
2nd rowStillImage
3rd rowStillImage
4th rowStillImage
5th rowStillImage
ValueCountFrequency (%)
stillimage 11788
84.2%
stillimage;stillimage 1471
 
10.5%
stillimage;stillimage;stillimage 245
 
1.7%
stillimage;stillimage;stillimage;stillimage 193
 
1.4%
stillimage;stillimage;stillimage;stillimage;stillimage 97
 
0.7%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 75
 
0.5%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 45
 
0.3%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 18
 
0.1%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 16
 
0.1%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 12
 
0.1%
Other values (9) 44
 
0.3%
2025-01-08T17:43:09.309519image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 37966
19.5%
S 18983
9.7%
t 18983
9.7%
i 18983
9.7%
I 18983
9.7%
m 18983
9.7%
a 18983
9.7%
g 18983
9.7%
e 18983
9.7%
; 4979
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 151864
78.0%
Uppercase Letter 37966
 
19.5%
Other Punctuation 4979
 
2.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 37966
25.0%
t 18983
12.5%
i 18983
12.5%
m 18983
12.5%
a 18983
12.5%
g 18983
12.5%
e 18983
12.5%
Uppercase Letter
ValueCountFrequency (%)
S 18983
50.0%
I 18983
50.0%
Other Punctuation
ValueCountFrequency (%)
; 4979
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 189830
97.4%
Common 4979
 
2.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 37966
20.0%
S 18983
10.0%
t 18983
10.0%
i 18983
10.0%
I 18983
10.0%
m 18983
10.0%
a 18983
10.0%
g 18983
10.0%
e 18983
10.0%
Common
ValueCountFrequency (%)
; 4979
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 194809
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 37966
19.5%
S 18983
9.7%
t 18983
9.7%
i 18983
9.7%
I 18983
9.7%
m 18983
9.7%
a 18983
9.7%
g 18983
9.7%
e 18983
9.7%
; 4979
 
2.6%
Distinct2
Distinct (%)< 0.1%
Missing5
Missing (%)< 0.1%
Memory size2.6 MiB
2025-01-08T17:43:09.352810image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.217271192
Min length4

Characters and Unicode

Total characters1425813
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowtrue
2nd rowtrue
3rd rowtrue
4th rowfalse
5th rowtrue
ValueCountFrequency (%)
true 264632
78.3%
false 73457
 
21.7%
2025-01-08T17:43:09.445146image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 338089
23.7%
t 264632
18.6%
r 264632
18.6%
u 264632
18.6%
f 73457
 
5.2%
a 73457
 
5.2%
l 73457
 
5.2%
s 73457
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1425813
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 338089
23.7%
t 264632
18.6%
r 264632
18.6%
u 264632
18.6%
f 73457
 
5.2%
a 73457
 
5.2%
l 73457
 
5.2%
s 73457
 
5.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 1425813
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 338089
23.7%
t 264632
18.6%
r 264632
18.6%
u 264632
18.6%
f 73457
 
5.2%
a 73457
 
5.2%
l 73457
 
5.2%
s 73457
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1425813
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 338089
23.7%
t 264632
18.6%
r 264632
18.6%
u 264632
18.6%
f 73457
 
5.2%
a 73457
 
5.2%
l 73457
 
5.2%
s 73457
 
5.2%
Distinct2
Distinct (%)< 0.1%
Missing5
Missing (%)< 0.1%
Memory size2.6 MiB
2025-01-08T17:43:09.485145image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.992439861
Min length4

Characters and Unicode

Total characters1687889
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowfalse
2nd rowfalse
3rd rowfalse
4th rowfalse
5th rowfalse
ValueCountFrequency (%)
false 335533
99.2%
true 2556
 
0.8%
2025-01-08T17:43:09.585441image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 338089
20.0%
f 335533
19.9%
a 335533
19.9%
l 335533
19.9%
s 335533
19.9%
t 2556
 
0.2%
r 2556
 
0.2%
u 2556
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1687889
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 338089
20.0%
f 335533
19.9%
a 335533
19.9%
l 335533
19.9%
s 335533
19.9%
t 2556
 
0.2%
r 2556
 
0.2%
u 2556
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 1687889
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 338089
20.0%
f 335533
19.9%
a 335533
19.9%
l 335533
19.9%
s 335533
19.9%
t 2556
 
0.2%
r 2556
 
0.2%
u 2556
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1687889
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 338089
20.0%
f 335533
19.9%
a 335533
19.9%
l 335533
19.9%
s 335533
19.9%
t 2556
 
0.2%
r 2556
 
0.2%
u 2556
 
0.2%
Distinct45746
Distinct (%)13.5%
Missing5
Missing (%)< 0.1%
Memory size2.6 MiB
2025-01-08T17:43:09.769919image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length7
Mean length6.660985717
Min length1

Characters and Unicode

Total characters2252006
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9824 ?
Unique (%)2.9%

Sample

1st row10583418
2nd row5854277
3rd row5771
4th row4479
5th row2651085
ValueCountFrequency (%)
0 6107
 
1.8%
6841 3252
 
1.0%
637 2297
 
0.7%
2285664 2008
 
0.6%
2329589 2006
 
0.6%
2440447 1919
 
0.6%
8324617 1660
 
0.5%
7971837 1474
 
0.4%
2431491 1334
 
0.4%
2307333 1035
 
0.3%
Other values (45736) 314997
93.2%
2025-01-08T17:43:10.021715image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 349816
15.5%
1 269425
12.0%
4 234301
10.4%
3 228411
10.1%
7 210859
9.4%
5 205314
9.1%
8 200618
8.9%
9 192840
8.6%
0 183611
8.2%
6 176811
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2252006
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 349816
15.5%
1 269425
12.0%
4 234301
10.4%
3 228411
10.1%
7 210859
9.4%
5 205314
9.1%
8 200618
8.9%
9 192840
8.6%
0 183611
8.2%
6 176811
7.9%

Most occurring scripts

ValueCountFrequency (%)
Common 2252006
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 349816
15.5%
1 269425
12.0%
4 234301
10.4%
3 228411
10.1%
7 210859
9.4%
5 205314
9.1%
8 200618
8.9%
9 192840
8.6%
0 183611
8.2%
6 176811
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2252006
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 349816
15.5%
1 269425
12.0%
4 234301
10.4%
3 228411
10.1%
7 210859
9.4%
5 205314
9.1%
8 200618
8.9%
9 192840
8.6%
0 183611
8.2%
6 176811
7.9%

acceptedTaxonKey
Text

Missing 

Distinct44951
Distinct (%)13.5%
Missing6112
Missing (%)1.8%
Memory size2.6 MiB
2025-01-08T17:43:10.222972image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length7
Mean length6.770436349
Min length1

Characters and Unicode

Total characters2247663
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9417 ?
Unique (%)2.8%

Sample

1st row10583418
2nd row5854277
3rd row5771
4th row4479
5th row2651085
ValueCountFrequency (%)
6841 3252
 
1.0%
637 2297
 
0.7%
2285664 2008
 
0.6%
2329589 2006
 
0.6%
2440447 1919
 
0.6%
8324617 1660
 
0.5%
8770992 1474
 
0.4%
2431491 1334
 
0.4%
2307333 1035
 
0.3%
68 875
 
0.3%
Other values (44941) 314122
94.6%
2025-01-08T17:43:10.483783image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 335747
14.9%
1 273500
12.2%
4 233904
10.4%
3 226967
10.1%
5 207519
9.2%
7 206909
9.2%
8 206081
9.2%
9 198048
8.8%
0 180588
8.0%
6 178400
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2247663
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 335747
14.9%
1 273500
12.2%
4 233904
10.4%
3 226967
10.1%
5 207519
9.2%
7 206909
9.2%
8 206081
9.2%
9 198048
8.8%
0 180588
8.0%
6 178400
7.9%

Most occurring scripts

ValueCountFrequency (%)
Common 2247663
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 335747
14.9%
1 273500
12.2%
4 233904
10.4%
3 226967
10.1%
5 207519
9.2%
7 206909
9.2%
8 206081
9.2%
9 198048
8.8%
0 180588
8.0%
6 178400
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2247663
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 335747
14.9%
1 273500
12.2%
4 233904
10.4%
3 226967
10.1%
5 207519
9.2%
7 206909
9.2%
8 206081
9.2%
9 198048
8.8%
0 180588
8.0%
6 178400
7.9%
Distinct6
Distinct (%)< 0.1%
Missing5
Missing (%)< 0.1%
Memory size2.6 MiB
2025-01-08T17:43:10.544005image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters338089
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row6
ValueCountFrequency (%)
1 291926
86.3%
6 35530
 
10.5%
0 6107
 
1.8%
4 3038
 
0.9%
3 1166
 
0.3%
5 322
 
0.1%
2025-01-08T17:43:10.638864image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 291926
86.3%
6 35530
 
10.5%
0 6107
 
1.8%
4 3038
 
0.9%
3 1166
 
0.3%
5 322
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 338089
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 291926
86.3%
6 35530
 
10.5%
0 6107
 
1.8%
4 3038
 
0.9%
3 1166
 
0.3%
5 322
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 338089
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 291926
86.3%
6 35530
 
10.5%
0 6107
 
1.8%
4 3038
 
0.9%
3 1166
 
0.3%
5 322
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 338089
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 291926
86.3%
6 35530
 
10.5%
0 6107
 
1.8%
4 3038
 
0.9%
3 1166
 
0.3%
5 322
 
0.1%

phylumKey
Text

Missing 

Distinct40
Distinct (%)< 0.1%
Missing6812
Missing (%)2.0%
Memory size2.6 MiB
2025-01-08T17:43:10.691495image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length2
Mean length2.519107588
Min length1

Characters and Unicode

Total characters834535
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row54
2nd row42
3rd row42
4th row54
5th row7707728
ValueCountFrequency (%)
54 145971
44.1%
44 103372
31.2%
7707728 30584
 
9.2%
52 20737
 
6.3%
42 11327
 
3.4%
43 3177
 
1.0%
106 2942
 
0.9%
8770992 2110
 
0.6%
50 1630
 
0.5%
36 1622
 
0.5%
Other values (30) 7810
 
2.4%
2025-01-08T17:43:10.808969image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 368289
44.1%
5 171646
20.6%
7 127682
 
15.3%
2 65080
 
7.8%
0 39492
 
4.7%
8 36207
 
4.3%
6 7247
 
0.9%
3 7107
 
0.9%
1 5946
 
0.7%
9 5839
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 834535
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 368289
44.1%
5 171646
20.6%
7 127682
 
15.3%
2 65080
 
7.8%
0 39492
 
4.7%
8 36207
 
4.3%
6 7247
 
0.9%
3 7107
 
0.9%
1 5946
 
0.7%
9 5839
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
Common 834535
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 368289
44.1%
5 171646
20.6%
7 127682
 
15.3%
2 65080
 
7.8%
0 39492
 
4.7%
8 36207
 
4.3%
6 7247
 
0.9%
3 7107
 
0.9%
1 5946
 
0.7%
9 5839
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 834535
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 368289
44.1%
5 171646
20.6%
7 127682
 
15.3%
2 65080
 
7.8%
0 39492
 
4.7%
8 36207
 
4.3%
6 7247
 
0.9%
3 7107
 
0.9%
1 5946
 
0.7%
9 5839
 
0.7%

classKey
Text

Missing 

Distinct105
Distinct (%)< 0.1%
Missing52277
Missing (%)15.5%
Memory size2.6 MiB
2025-01-08T17:43:10.906316image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.277555219
Min length3

Characters and Unicode

Total characters936781
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st row216
2nd row256
3rd row256
4th row229
5th row7228684
ValueCountFrequency (%)
216 112951
39.5%
229 27895
 
9.8%
359 24478
 
8.6%
131 18384
 
6.4%
220 15795
 
5.5%
196 10876
 
3.8%
256 10686
 
3.7%
137 9771
 
3.4%
225 9525
 
3.3%
11592253 9481
 
3.3%
Other values (95) 35975
 
12.6%
2025-01-08T17:43:11.062190image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 285083
30.4%
1 210874
22.5%
6 146616
15.7%
9 79319
 
8.5%
3 77102
 
8.2%
5 74835
 
8.0%
0 24095
 
2.6%
7 19107
 
2.0%
4 11458
 
1.2%
8 8292
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 936781
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 285083
30.4%
1 210874
22.5%
6 146616
15.7%
9 79319
 
8.5%
3 77102
 
8.2%
5 74835
 
8.0%
0 24095
 
2.6%
7 19107
 
2.0%
4 11458
 
1.2%
8 8292
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
Common 936781
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 285083
30.4%
1 210874
22.5%
6 146616
15.7%
9 79319
 
8.5%
3 77102
 
8.2%
5 74835
 
8.0%
0 24095
 
2.6%
7 19107
 
2.0%
4 11458
 
1.2%
8 8292
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 936781
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 285083
30.4%
1 210874
22.5%
6 146616
15.7%
9 79319
 
8.5%
3 77102
 
8.2%
5 74835
 
8.0%
0 24095
 
2.6%
7 19107
 
2.0%
4 11458
 
1.2%
8 8292
 
0.9%

orderKey
Text

Missing 

Distinct531
Distinct (%)0.2%
Missing30347
Missing (%)9.0%
Memory size2.6 MiB
2025-01-08T17:43:11.234629image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.491471891
Min length3

Characters and Unicode

Total characters1074490
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)< 0.1%

Sample

1st row797
2nd row1080
3rd row864
4th row637
5th row392
ValueCountFrequency (%)
797 79519
25.8%
587 25783
 
8.4%
637 23755
 
7.7%
1470 10132
 
3.3%
952 10009
 
3.3%
1457 8496
 
2.8%
1459 8406
 
2.7%
953 8204
 
2.7%
1369 7858
 
2.6%
733 7808
 
2.5%
Other values (521) 117777
38.3%
2025-01-08T17:43:11.469083image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 281408
26.2%
9 172836
16.1%
1 111891
 
10.4%
3 100100
 
9.3%
5 91866
 
8.5%
4 74011
 
6.9%
8 71573
 
6.7%
0 64573
 
6.0%
6 63725
 
5.9%
2 42507
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1074490
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 281408
26.2%
9 172836
16.1%
1 111891
 
10.4%
3 100100
 
9.3%
5 91866
 
8.5%
4 74011
 
6.9%
8 71573
 
6.7%
0 64573
 
6.0%
6 63725
 
5.9%
2 42507
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1074490
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 281408
26.2%
9 172836
16.1%
1 111891
 
10.4%
3 100100
 
9.3%
5 91866
 
8.5%
4 74011
 
6.9%
8 71573
 
6.7%
0 64573
 
6.0%
6 63725
 
5.9%
2 42507
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1074490
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 281408
26.2%
9 172836
16.1%
1 111891
 
10.4%
3 100100
 
9.3%
5 91866
 
8.5%
4 74011
 
6.9%
8 71573
 
6.7%
0 64573
 
6.0%
6 63725
 
5.9%
2 42507
 
4.0%

familyKey
Text

Missing 

Distinct3094
Distinct (%)1.0%
Missing19910
Missing (%)5.9%
Memory size2.6 MiB
2025-01-08T17:43:11.663395image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length4
Mean length4.310185302
Min length4

Characters and Unicode

Total characters1371432
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique308 ?
Unique (%)0.1%

Sample

1st row4705755
2nd row5854277
3rd row5771
4th row4479
5th row2373
ValueCountFrequency (%)
4479 12102
 
3.8%
6950 12012
 
3.8%
7015 7500
 
2.4%
5343 7246
 
2.3%
6748 6784
 
2.1%
3073 6677
 
2.1%
5314 5540
 
1.7%
4532185 5452
 
1.7%
5854277 5009
 
1.6%
6841 4930
 
1.5%
Other values (3084) 244932
77.0%
2025-01-08T17:43:11.917709image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 190928
13.9%
4 186306
13.6%
3 170146
12.4%
7 153207
11.2%
6 142449
10.4%
8 120810
8.8%
9 112349
8.2%
2 107749
7.9%
0 97175
7.1%
1 90313
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1371432
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 190928
13.9%
4 186306
13.6%
3 170146
12.4%
7 153207
11.2%
6 142449
10.4%
8 120810
8.8%
9 112349
8.2%
2 107749
7.9%
0 97175
7.1%
1 90313
6.6%

Most occurring scripts

ValueCountFrequency (%)
Common 1371432
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 190928
13.9%
4 186306
13.6%
3 170146
12.4%
7 153207
11.2%
6 142449
10.4%
8 120810
8.8%
9 112349
8.2%
2 107749
7.9%
0 97175
7.1%
1 90313
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1371432
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 190928
13.9%
4 186306
13.6%
3 170146
12.4%
7 153207
11.2%
6 142449
10.4%
8 120810
8.8%
9 112349
8.2%
2 107749
7.9%
0 97175
7.1%
1 90313
6.6%

genusKey
Text

Missing 

Distinct19382
Distinct (%)6.4%
Missing34396
Missing (%)10.2%
Memory size2.6 MiB
2025-01-08T17:43:12.122247image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length7
Mean length7.00830101
Min length7

Characters and Unicode

Total characters2128407
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2161 ?
Unique (%)0.7%

Sample

1st row4686308
2nd row2651085
3rd row1068113
4th row4609405
5th row2406899
ValueCountFrequency (%)
2431477 4671
 
1.5%
4646327 4236
 
1.4%
2227127 3675
 
1.2%
2285664 2587
 
0.9%
2329589 2006
 
0.7%
2440446 1919
 
0.6%
2227317 1707
 
0.6%
2440326 1662
 
0.5%
4312471 1424
 
0.5%
8782549 1420
 
0.5%
Other values (19372) 278391
91.7%
2025-01-08T17:43:12.511037image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 352255
16.6%
4 258075
12.1%
1 241765
11.4%
3 237700
11.2%
7 202632
9.5%
8 184073
8.6%
9 172673
8.1%
6 170699
8.0%
5 157110
7.4%
0 151425
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2128407
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 352255
16.6%
4 258075
12.1%
1 241765
11.4%
3 237700
11.2%
7 202632
9.5%
8 184073
8.6%
9 172673
8.1%
6 170699
8.0%
5 157110
7.4%
0 151425
7.1%

Most occurring scripts

ValueCountFrequency (%)
Common 2128407
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 352255
16.6%
4 258075
12.1%
1 241765
11.4%
3 237700
11.2%
7 202632
9.5%
8 184073
8.6%
9 172673
8.1%
6 170699
8.0%
5 157110
7.4%
0 151425
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2128407
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 352255
16.6%
4 258075
12.1%
1 241765
11.4%
3 237700
11.2%
7 202632
9.5%
8 184073
8.6%
9 172673
8.1%
6 170699
8.0%
5 157110
7.4%
0 151425
7.1%

speciesKey
Text

Missing 

Distinct37032
Distinct (%)14.9%
Missing89520
Missing (%)26.5%
Memory size2.6 MiB
2025-01-08T17:43:12.725182image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length7
Mean length7.043576561
Min length7

Characters and Unicode

Total characters1750850
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7679 ?
Unique (%)3.1%

Sample

1st row10583418
2nd row1068127
3rd row11155573
4th row2406900
5th row6788608
ValueCountFrequency (%)
2440447 1919
 
0.8%
8324617 1660
 
0.7%
2431491 1334
 
0.5%
2431423 815
 
0.3%
2432006 764
 
0.3%
2431513 639
 
0.3%
5218985 601
 
0.2%
9001095 579
 
0.2%
4312492 579
 
0.2%
2431543 566
 
0.2%
Other values (37022) 239118
96.2%
2025-01-08T17:43:12.983676image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 263968
15.1%
1 217498
12.4%
4 185797
10.6%
3 173534
9.9%
5 166110
9.5%
8 162114
9.3%
7 157335
9.0%
9 155062
8.9%
0 141342
8.1%
6 128090
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1750850
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 263968
15.1%
1 217498
12.4%
4 185797
10.6%
3 173534
9.9%
5 166110
9.5%
8 162114
9.3%
7 157335
9.0%
9 155062
8.9%
0 141342
8.1%
6 128090
7.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1750850
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 263968
15.1%
1 217498
12.4%
4 185797
10.6%
3 173534
9.9%
5 166110
9.5%
8 162114
9.3%
7 157335
9.0%
9 155062
8.9%
0 141342
8.1%
6 128090
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1750850
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 263968
15.1%
1 217498
12.4%
4 185797
10.6%
3 173534
9.9%
5 166110
9.5%
8 162114
9.3%
7 157335
9.0%
9 155062
8.9%
0 141342
8.1%
6 128090
7.3%

species
Text

Missing 

Distinct37025
Distinct (%)14.9%
Missing89520
Missing (%)26.5%
Memory size2.6 MiB
2025-01-08T17:43:13.182383image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length36
Median length30
Mean length19.21962474
Min length8

Characters and Unicode

Total characters4777499
Distinct characters54
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7675 ?
Unique (%)3.1%

Sample

1st rowRectiostoma fernaldella
2nd rowMesontoplatys bolzi
3rd rowDulcerana granularis
4th rowAmanses scopas
5th rowCalyptogena extenta
ValueCountFrequency (%)
plethodon 4564
 
0.9%
faxonius 4236
 
0.9%
procambarus 3408
 
0.7%
truncatus 1929
 
0.4%
tursiops 1919
 
0.4%
cinereus 1885
 
0.4%
delphis 1660
 
0.3%
delphinus 1660
 
0.3%
cambarus 1583
 
0.3%
anolis 1411
 
0.3%
Other values (38206) 472895
95.1%
2025-01-08T17:43:13.444628image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 541195
 
11.3%
i 417200
 
8.7%
s 361384
 
7.6%
e 336874
 
7.1%
o 316429
 
6.6%
r 303496
 
6.4%
l 260561
 
5.5%
248576
 
5.2%
n 248318
 
5.2%
u 245629
 
5.1%
Other values (44) 1497837
31.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4280184
89.6%
Uppercase Letter 248580
 
5.2%
Space Separator 248576
 
5.2%
Dash Punctuation 159
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 541195
12.6%
i 417200
9.7%
s 361384
 
8.4%
e 336874
 
7.9%
o 316429
 
7.4%
r 303496
 
7.1%
l 260561
 
6.1%
n 248318
 
5.8%
u 245629
 
5.7%
t 241459
 
5.6%
Other values (16) 1007639
23.5%
Uppercase Letter
ValueCountFrequency (%)
P 39940
16.1%
C 30327
12.2%
A 26578
10.7%
S 20139
 
8.1%
M 15848
 
6.4%
E 14671
 
5.9%
L 12774
 
5.1%
H 12456
 
5.0%
T 11171
 
4.5%
D 11092
 
4.5%
Other values (16) 53584
21.6%
Space Separator
ValueCountFrequency (%)
248576
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 159
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4528764
94.8%
Common 248735
 
5.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 541195
12.0%
i 417200
 
9.2%
s 361384
 
8.0%
e 336874
 
7.4%
o 316429
 
7.0%
r 303496
 
6.7%
l 260561
 
5.8%
n 248318
 
5.5%
u 245629
 
5.4%
t 241459
 
5.3%
Other values (42) 1256219
27.7%
Common
ValueCountFrequency (%)
248576
99.9%
- 159
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4777499
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 541195
 
11.3%
i 417200
 
8.7%
s 361384
 
7.6%
e 336874
 
7.1%
o 316429
 
6.6%
r 303496
 
6.4%
l 260561
 
5.5%
248576
 
5.2%
n 248318
 
5.2%
u 245629
 
5.1%
Other values (44) 1497837
31.4%
Distinct44951
Distinct (%)13.5%
Missing6112
Missing (%)1.8%
Memory size2.6 MiB
2025-01-08T17:43:13.650554image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length136
Median length90
Mean length31.13227826
Min length5

Characters and Unicode

Total characters10335356
Distinct characters107
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9417 ?
Unique (%)2.8%

Sample

1st rowRectiostoma fernaldella
2nd rowSiboglinidae
3rd rowAmphinomidae
4th rowCambaridae
5th rowPolystichum Roth
ValueCountFrequency (%)
37558
 
3.0%
linnaeus 10225
 
0.8%
1758 8032
 
0.6%
l 6309
 
0.5%
1985 5095
 
0.4%
plethodon 4673
 
0.4%
walker 4511
 
0.4%
jones 4350
 
0.3%
faxonius 4236
 
0.3%
procambarus 3675
 
0.3%
Other values (49762) 1162095
92.9%
2025-01-08T17:43:13.923301image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
918777
 
8.9%
a 834408
 
8.1%
e 661550
 
6.4%
i 629479
 
6.1%
r 530385
 
5.1%
s 523738
 
5.1%
o 514156
 
5.0%
n 463991
 
4.5%
l 422188
 
4.1%
t 361951
 
3.5%
Other values (97) 4474733
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6989605
67.6%
Decimal Number 1045012
 
10.1%
Space Separator 918777
 
8.9%
Uppercase Letter 744301
 
7.2%
Other Punctuation 380647
 
3.7%
Close Punctuation 126253
 
1.2%
Open Punctuation 126253
 
1.2%
Dash Punctuation 4427
 
< 0.1%
Math Symbol 78
 
< 0.1%
Connector Punctuation 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 834408
11.9%
e 661550
 
9.5%
i 629479
 
9.0%
r 530385
 
7.6%
s 523738
 
7.5%
o 514156
 
7.4%
n 463991
 
6.6%
l 422188
 
6.0%
t 361951
 
5.2%
u 355648
 
5.1%
Other values (43) 1692111
24.2%
Uppercase Letter
ValueCountFrequency (%)
P 65471
 
8.8%
C 64551
 
8.7%
B 58203
 
7.8%
S 57866
 
7.8%
L 52865
 
7.1%
M 50300
 
6.8%
H 47242
 
6.3%
A 47144
 
6.3%
G 43860
 
5.9%
D 38280
 
5.1%
Other values (24) 218519
29.4%
Decimal Number
ValueCountFrequency (%)
1 307284
29.4%
8 202570
19.4%
9 141944
13.6%
7 72354
 
6.9%
2 62471
 
6.0%
0 62196
 
6.0%
5 60671
 
5.8%
6 50352
 
4.8%
3 46493
 
4.4%
4 38677
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 266394
70.0%
. 76357
 
20.1%
& 37558
 
9.9%
' 338
 
0.1%
Space Separator
ValueCountFrequency (%)
918777
100.0%
Close Punctuation
ValueCountFrequency (%)
) 126253
100.0%
Open Punctuation
ValueCountFrequency (%)
( 126253
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4427
100.0%
Math Symbol
ValueCountFrequency (%)
× 78
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7733906
74.8%
Common 2601450
 
25.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 834408
 
10.8%
e 661550
 
8.6%
i 629479
 
8.1%
r 530385
 
6.9%
s 523738
 
6.8%
o 514156
 
6.6%
n 463991
 
6.0%
l 422188
 
5.5%
t 361951
 
4.7%
u 355648
 
4.6%
Other values (77) 2436412
31.5%
Common
ValueCountFrequency (%)
918777
35.3%
1 307284
 
11.8%
, 266394
 
10.2%
8 202570
 
7.8%
9 141944
 
5.5%
) 126253
 
4.9%
( 126253
 
4.9%
. 76357
 
2.9%
7 72354
 
2.8%
2 62471
 
2.4%
Other values (10) 300793
 
11.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10311871
99.8%
None 23485
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
918777
 
8.9%
a 834408
 
8.1%
e 661550
 
6.4%
i 629479
 
6.1%
r 530385
 
5.1%
s 523738
 
5.1%
o 514156
 
5.0%
n 463991
 
4.5%
l 422188
 
4.1%
t 361951
 
3.5%
Other values (61) 4451248
43.2%
None
ValueCountFrequency (%)
ü 8130
34.6%
é 6105
26.0%
è 2347
 
10.0%
ö 1932
 
8.2%
å 1562
 
6.7%
ä 831
 
3.5%
ó 715
 
3.0%
á 474
 
2.0%
ø 310
 
1.3%
É 261
 
1.1%
Other values (26) 818
 
3.5%
Distinct46008
Distinct (%)14.6%
Missing24039
Missing (%)7.1%
Memory size2.6 MiB
2025-01-08T17:43:14.111136image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length85
Median length63
Mean length18.57454904
Min length3

Characters and Unicode

Total characters5833430
Distinct characters79
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10055 ?
Unique (%)3.2%

Sample

1st rowRectiostoma fernaldella
2nd rowPolystichum sp.
3rd rowMesontoplatys bolzi
4th rowBursa granularis
5th rowAmanses scopas
ValueCountFrequency (%)
sp 50633
 
7.9%
plethodon 4673
 
0.7%
orconectes 4548
 
0.7%
indet 4202
 
0.7%
procambarus 3784
 
0.6%
unidentified 3701
 
0.6%
bathymodiolus 2598
 
0.4%
cinereus 2325
 
0.4%
riftia 2006
 
0.3%
truncatus 1926
 
0.3%
Other values (42984) 556915
87.4%
2025-01-08T17:43:14.358556image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 627231
 
10.8%
i 493887
 
8.5%
s 465451
 
8.0%
e 411782
 
7.1%
o 369786
 
6.3%
r 352399
 
6.0%
323256
 
5.5%
l 300021
 
5.1%
n 294984
 
5.1%
t 291085
 
5.0%
Other values (69) 1903548
32.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5130026
87.9%
Space Separator 323256
 
5.5%
Uppercase Letter 316733
 
5.4%
Other Punctuation 57342
 
1.0%
Open Punctuation 2361
 
< 0.1%
Close Punctuation 2361
 
< 0.1%
Decimal Number 880
 
< 0.1%
Connector Punctuation 279
 
< 0.1%
Dash Punctuation 192
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 627231
12.2%
i 493887
 
9.6%
s 465451
 
9.1%
e 411782
 
8.0%
o 369786
 
7.2%
r 352399
 
6.9%
l 300021
 
5.8%
n 294984
 
5.8%
t 291085
 
5.7%
u 273206
 
5.3%
Other values (19) 1250194
24.4%
Uppercase Letter
ValueCountFrequency (%)
P 48084
15.2%
C 36649
11.6%
A 33460
10.6%
S 23813
 
7.5%
M 18809
 
5.9%
E 17848
 
5.6%
L 16380
 
5.2%
H 16021
 
5.1%
T 14035
 
4.4%
D 13545
 
4.3%
Other values (17) 78089
24.7%
Decimal Number
ValueCountFrequency (%)
0 270
30.7%
1 264
30.0%
2 99
 
11.2%
3 65
 
7.4%
6 56
 
6.4%
7 46
 
5.2%
8 26
 
3.0%
4 23
 
2.6%
5 17
 
1.9%
9 14
 
1.6%
Other Punctuation
ValueCountFrequency (%)
. 56693
98.9%
" 304
 
0.5%
' 250
 
0.4%
, 65
 
0.1%
/ 13
 
< 0.1%
& 11
 
< 0.1%
? 5
 
< 0.1%
# 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
323256
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2361
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2361
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 279
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 192
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5446759
93.4%
Common 386671
 
6.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 627231
11.5%
i 493887
 
9.1%
s 465451
 
8.5%
e 411782
 
7.6%
o 369786
 
6.8%
r 352399
 
6.5%
l 300021
 
5.5%
n 294984
 
5.4%
t 291085
 
5.3%
u 273206
 
5.0%
Other values (46) 1566927
28.8%
Common
ValueCountFrequency (%)
323256
83.6%
. 56693
 
14.7%
( 2361
 
0.6%
) 2361
 
0.6%
" 304
 
0.1%
_ 279
 
0.1%
0 270
 
0.1%
1 264
 
0.1%
' 250
 
0.1%
- 192
 
< 0.1%
Other values (13) 441
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5833417
> 99.9%
None 13
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 627231
 
10.8%
i 493887
 
8.5%
s 465451
 
8.0%
e 411782
 
7.1%
o 369786
 
6.3%
r 352399
 
6.0%
323256
 
5.5%
l 300021
 
5.1%
n 294984
 
5.1%
t 291085
 
5.0%
Other values (65) 1903535
32.6%
None
ValueCountFrequency (%)
ë 9
69.2%
ö 2
 
15.4%
Á 1
 
7.7%
é 1
 
7.7%

typifiedName
Text

Missing 

Distinct13
Distinct (%)38.2%
Missing338060
Missing (%)> 99.9%
Memory size2.6 MiB
2025-01-08T17:43:14.428483image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length11
Mean length9.352941176
Min length5

Characters and Unicode

Total characters318
Distinct characters29
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowJaponica
2nd rowPallidata
3rd rowLepidophaga
4th rowDives
5th rowFurcifer
ValueCountFrequency (%)
lepidophaga 4
11.8%
dives 4
11.8%
tartarella 4
11.8%
inexpectata 4
11.8%
japonica 2
 
5.9%
pallidata 2
 
5.9%
furcifer 2
 
5.9%
pervada 2
 
5.9%
echinopanicis 2
 
5.9%
ruptifascia 2
 
5.9%
Other values (3) 6
17.6%
2025-01-08T17:43:14.558088image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 56
17.6%
i 28
 
8.8%
e 28
 
8.8%
t 20
 
6.3%
r 20
 
6.3%
p 18
 
5.7%
l 18
 
5.7%
o 16
 
5.0%
n 14
 
4.4%
c 14
 
4.4%
Other values (19) 86
27.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 284
89.3%
Uppercase Letter 34
 
10.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 56
19.7%
i 28
9.9%
e 28
9.9%
t 20
 
7.0%
r 20
 
7.0%
p 18
 
6.3%
l 18
 
6.3%
o 16
 
5.6%
n 14
 
4.9%
c 14
 
4.9%
Other values (8) 52
18.3%
Uppercase Letter
ValueCountFrequency (%)
T 6
17.6%
P 4
11.8%
L 4
11.8%
I 4
11.8%
D 4
11.8%
J 2
 
5.9%
F 2
 
5.9%
E 2
 
5.9%
R 2
 
5.9%
C 2
 
5.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 318
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 56
17.6%
i 28
 
8.8%
e 28
 
8.8%
t 20
 
6.3%
r 20
 
6.3%
p 18
 
5.7%
l 18
 
5.7%
o 16
 
5.0%
n 14
 
4.4%
c 14
 
4.4%
Other values (19) 86
27.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 318
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 56
17.6%
i 28
 
8.8%
e 28
 
8.8%
t 20
 
6.3%
r 20
 
6.3%
p 18
 
5.7%
l 18
 
5.7%
o 16
 
5.0%
n 14
 
4.4%
c 14
 
4.4%
Other values (19) 86
27.0%

protocol
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing5
Missing (%)< 0.1%
Memory size2.6 MiB
2025-01-08T17:43:14.601088image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1014267
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEML
2nd rowEML
3rd rowEML
4th rowEML
5th rowEML
ValueCountFrequency (%)
eml 338089
100.0%
2025-01-08T17:43:14.694800image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 338089
33.3%
M 338089
33.3%
L 338089
33.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1014267
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 338089
33.3%
M 338089
33.3%
L 338089
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 1014267
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 338089
33.3%
M 338089
33.3%
L 338089
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1014267
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 338089
33.3%
M 338089
33.3%
L 338089
33.3%
Distinct31887
Distinct (%)9.4%
Missing5
Missing (%)< 0.1%
Memory size2.6 MiB
2025-01-08T17:43:14.796528image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length24
Mean length23.99607204
Min length20

Characters and Unicode

Total characters8112808
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3500 ?
Unique (%)1.0%

Sample

1st row2024-12-01T12:07:01.240Z
2nd row2024-12-01T12:07:01.438Z
3rd row2024-12-01T12:07:01.443Z
4th row2024-12-01T12:07:01.449Z
5th row2024-12-01T12:07:01.465Z
ValueCountFrequency (%)
2024-12-01t12:07:38.532z 73
 
< 0.1%
2024-12-01t12:07:38.533z 71
 
< 0.1%
2024-12-01t12:07:38.508z 68
 
< 0.1%
2024-12-01t12:07:39.879z 67
 
< 0.1%
2024-12-01t12:07:39.819z 65
 
< 0.1%
2024-12-01t12:07:37.936z 65
 
< 0.1%
2024-12-01t12:07:40.339z 65
 
< 0.1%
2024-12-01t12:07:39.875z 64
 
< 0.1%
2024-12-01t12:07:39.723z 64
 
< 0.1%
2024-12-01t12:07:38.854z 63
 
< 0.1%
Other values (31877) 337424
99.8%
2025-01-08T17:43:14.969952image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1562001
19.3%
1 1172147
14.4%
0 1166550
14.4%
- 676178
8.3%
: 676178
8.3%
4 503489
 
6.2%
7 475460
 
5.9%
T 338089
 
4.2%
Z 338089
 
4.2%
. 337757
 
4.2%
Other values (5) 866870
10.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5746517
70.8%
Other Punctuation 1013935
 
12.5%
Dash Punctuation 676178
 
8.3%
Uppercase Letter 676178
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1562001
27.2%
1 1172147
20.4%
0 1166550
20.3%
4 503489
 
8.8%
7 475460
 
8.3%
3 314692
 
5.5%
8 145833
 
2.5%
9 145808
 
2.5%
6 137824
 
2.4%
5 122713
 
2.1%
Other Punctuation
ValueCountFrequency (%)
: 676178
66.7%
. 337757
33.3%
Uppercase Letter
ValueCountFrequency (%)
T 338089
50.0%
Z 338089
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 676178
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7436630
91.7%
Latin 676178
 
8.3%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1562001
21.0%
1 1172147
15.8%
0 1166550
15.7%
- 676178
9.1%
: 676178
9.1%
4 503489
 
6.8%
7 475460
 
6.4%
. 337757
 
4.5%
3 314692
 
4.2%
8 145833
 
2.0%
Other values (3) 406345
 
5.5%
Latin
ValueCountFrequency (%)
T 338089
50.0%
Z 338089
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8112808
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1562001
19.3%
1 1172147
14.4%
0 1166550
14.4%
- 676178
8.3%
: 676178
8.3%
4 503489
 
6.2%
7 475460
 
5.9%
T 338089
 
4.2%
Z 338089
 
4.2%
. 337757
 
4.2%
Other values (5) 866870
10.7%

lastCrawled
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing5
Missing (%)< 0.1%
Memory size2.6 MiB
2025-01-08T17:43:15.026951image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters8114136
Distinct characters10
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-12-01T11:07:21.711Z
2nd row2024-12-01T11:07:21.711Z
3rd row2024-12-01T11:07:21.711Z
4th row2024-12-01T11:07:21.711Z
5th row2024-12-01T11:07:21.711Z
ValueCountFrequency (%)
2024-12-01t11:07:21.711z 338089
100.0%
2025-01-08T17:43:15.126193image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2366623
29.2%
2 1352356
16.7%
0 1014267
12.5%
- 676178
 
8.3%
: 676178
 
8.3%
7 676178
 
8.3%
4 338089
 
4.2%
T 338089
 
4.2%
. 338089
 
4.2%
Z 338089
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5747513
70.8%
Other Punctuation 1014267
 
12.5%
Dash Punctuation 676178
 
8.3%
Uppercase Letter 676178
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2366623
41.2%
2 1352356
23.5%
0 1014267
17.6%
7 676178
 
11.8%
4 338089
 
5.9%
Other Punctuation
ValueCountFrequency (%)
: 676178
66.7%
. 338089
33.3%
Uppercase Letter
ValueCountFrequency (%)
T 338089
50.0%
Z 338089
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 676178
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7437958
91.7%
Latin 676178
 
8.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2366623
31.8%
2 1352356
18.2%
0 1014267
13.6%
- 676178
 
9.1%
: 676178
 
9.1%
7 676178
 
9.1%
4 338089
 
4.5%
. 338089
 
4.5%
Latin
ValueCountFrequency (%)
T 338089
50.0%
Z 338089
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8114136
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2366623
29.2%
2 1352356
16.7%
0 1014267
12.5%
- 676178
 
8.3%
: 676178
 
8.3%
7 676178
 
8.3%
4 338089
 
4.2%
T 338089
 
4.2%
. 338089
 
4.2%
Z 338089
 
4.2%

repatriated
Text

Missing 

Distinct2
Distinct (%)< 0.1%
Missing10837
Missing (%)3.2%
Memory size2.6 MiB
2025-01-08T17:43:15.167020image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.461276611
Min length4

Characters and Unicode

Total characters1459984
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowfalse
2nd rowtrue
3rd rowtrue
4th rowfalse
5th rowtrue
ValueCountFrequency (%)
true 176301
53.9%
false 150956
46.1%
2025-01-08T17:43:15.261353image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 327257
22.4%
t 176301
12.1%
r 176301
12.1%
u 176301
12.1%
f 150956
10.3%
a 150956
10.3%
l 150956
10.3%
s 150956
10.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1459984
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 327257
22.4%
t 176301
12.1%
r 176301
12.1%
u 176301
12.1%
f 150956
10.3%
a 150956
10.3%
l 150956
10.3%
s 150956
10.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 1459984
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 327257
22.4%
t 176301
12.1%
r 176301
12.1%
u 176301
12.1%
f 150956
10.3%
a 150956
10.3%
l 150956
10.3%
s 150956
10.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1459984
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 327257
22.4%
t 176301
12.1%
r 176301
12.1%
u 176301
12.1%
f 150956
10.3%
a 150956
10.3%
l 150956
10.3%
s 150956
10.3%
Distinct2
Distinct (%)< 0.1%
Missing5
Missing (%)< 0.1%
Memory size2.6 MiB
2025-01-08T17:43:15.301353image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.789076249
Min length4

Characters and Unicode

Total characters1619134
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowtrue
2nd rowfalse
3rd rowfalse
4th rowfalse
5th rowfalse
ValueCountFrequency (%)
false 266778
78.9%
true 71311
 
21.1%
2025-01-08T17:43:15.391104image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 338089
20.9%
f 266778
16.5%
a 266778
16.5%
l 266778
16.5%
s 266778
16.5%
t 71311
 
4.4%
r 71311
 
4.4%
u 71311
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1619134
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 338089
20.9%
f 266778
16.5%
a 266778
16.5%
l 266778
16.5%
s 266778
16.5%
t 71311
 
4.4%
r 71311
 
4.4%
u 71311
 
4.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 1619134
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 338089
20.9%
f 266778
16.5%
a 266778
16.5%
l 266778
16.5%
s 266778
16.5%
t 71311
 
4.4%
r 71311
 
4.4%
u 71311
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1619134
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 338089
20.9%
f 266778
16.5%
a 266778
16.5%
l 266778
16.5%
s 266778
16.5%
t 71311
 
4.4%
r 71311
 
4.4%
u 71311
 
4.4%

gbifRegion
Text

Missing 

Distinct7
Distinct (%)< 0.1%
Missing12220
Missing (%)3.6%
Memory size2.6 MiB
2025-01-08T17:43:15.438783image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length10.89375035
Min length4

Characters and Unicode

Total characters3549990
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNORTH_AMERICA
2nd rowLATIN_AMERICA
3rd rowOCEANIA
4th rowNORTH_AMERICA
5th rowASIA
ValueCountFrequency (%)
north_america 153734
47.2%
latin_america 78014
23.9%
oceania 37070
 
11.4%
asia 32944
 
10.1%
africa 17920
 
5.5%
europe 5860
 
1.8%
antarctica 332
 
0.1%
2025-01-08T17:43:15.540852image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 718374
20.2%
R 409594
11.5%
I 398028
11.2%
C 287402
8.1%
E 280538
 
7.9%
N 269150
 
7.6%
T 232412
 
6.5%
_ 231748
 
6.5%
M 231748
 
6.5%
O 196664
 
5.5%
Other values (6) 294332
8.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3318242
93.5%
Connector Punctuation 231748
 
6.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 718374
21.6%
R 409594
12.3%
I 398028
12.0%
C 287402
8.7%
E 280538
 
8.5%
N 269150
 
8.1%
T 232412
 
7.0%
M 231748
 
7.0%
O 196664
 
5.9%
H 153734
 
4.6%
Other values (5) 140598
 
4.2%
Connector Punctuation
ValueCountFrequency (%)
_ 231748
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3318242
93.5%
Common 231748
 
6.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 718374
21.6%
R 409594
12.3%
I 398028
12.0%
C 287402
8.7%
E 280538
 
8.5%
N 269150
 
8.1%
T 232412
 
7.0%
M 231748
 
7.0%
O 196664
 
5.9%
H 153734
 
4.6%
Other values (5) 140598
 
4.2%
Common
ValueCountFrequency (%)
_ 231748
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3549990
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 718374
20.2%
R 409594
11.5%
I 398028
11.2%
C 287402
8.1%
E 280538
 
7.9%
N 269150
 
7.6%
T 232412
 
6.5%
_ 231748
 
6.5%
M 231748
 
6.5%
O 196664
 
5.5%
Other values (6) 294332
8.3%

publishedByGbifRegion
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing5
Missing (%)< 0.1%
Memory size2.6 MiB
2025-01-08T17:43:15.587852image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters4395157
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNORTH_AMERICA
2nd rowNORTH_AMERICA
3rd rowNORTH_AMERICA
4th rowNORTH_AMERICA
5th rowNORTH_AMERICA
ValueCountFrequency (%)
north_america 338089
100.0%
2025-01-08T17:43:15.684273image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
R 676178
15.4%
A 676178
15.4%
N 338089
7.7%
O 338089
7.7%
T 338089
7.7%
H 338089
7.7%
_ 338089
7.7%
M 338089
7.7%
E 338089
7.7%
I 338089
7.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 4057068
92.3%
Connector Punctuation 338089
 
7.7%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 676178
16.7%
A 676178
16.7%
N 338089
8.3%
O 338089
8.3%
T 338089
8.3%
H 338089
8.3%
M 338089
8.3%
E 338089
8.3%
I 338089
8.3%
C 338089
8.3%
Connector Punctuation
ValueCountFrequency (%)
_ 338089
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4057068
92.3%
Common 338089
 
7.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
R 676178
16.7%
A 676178
16.7%
N 338089
8.3%
O 338089
8.3%
T 338089
8.3%
H 338089
8.3%
M 338089
8.3%
E 338089
8.3%
I 338089
8.3%
C 338089
8.3%
Common
ValueCountFrequency (%)
_ 338089
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4395157
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R 676178
15.4%
A 676178
15.4%
N 338089
7.7%
O 338089
7.7%
T 338089
7.7%
H 338089
7.7%
_ 338089
7.7%
M 338089
7.7%
E 338089
7.7%
I 338089
7.7%

level0Gid
Text

Missing 

Distinct174
Distinct (%)0.1%
Missing157741
Missing (%)46.7%
Memory size2.6 MiB
2025-01-08T17:43:15.822005image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters541059
Distinct characters28
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st rowUSA
2nd rowCHN
3rd rowKEN
4th rowDJI
5th rowUSA
ValueCountFrequency (%)
usa 97215
53.9%
mmr 7455
 
4.1%
mex 4807
 
2.7%
guy 4333
 
2.4%
phl 4062
 
2.3%
pyf 3614
 
2.0%
chn 3325
 
1.8%
bra 2654
 
1.5%
sur 2611
 
1.4%
mdg 2411
 
1.3%
Other values (164) 47866
26.5%
2025-01-08T17:43:16.017640image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 113189
20.9%
U 111068
20.5%
S 106325
19.7%
M 27389
 
5.1%
R 20032
 
3.7%
P 16725
 
3.1%
G 16411
 
3.0%
N 16119
 
3.0%
C 13892
 
2.6%
E 11267
 
2.1%
Other values (18) 88642
16.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 541053
> 99.9%
Decimal Number 6
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 113189
20.9%
U 111068
20.5%
S 106325
19.7%
M 27389
 
5.1%
R 20032
 
3.7%
P 16725
 
3.1%
G 16411
 
3.0%
N 16119
 
3.0%
C 13892
 
2.6%
E 11267
 
2.1%
Other values (16) 88636
16.4%
Decimal Number
ValueCountFrequency (%)
0 3
50.0%
7 3
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 541053
> 99.9%
Common 6
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 113189
20.9%
U 111068
20.5%
S 106325
19.7%
M 27389
 
5.1%
R 20032
 
3.7%
P 16725
 
3.1%
G 16411
 
3.0%
N 16119
 
3.0%
C 13892
 
2.6%
E 11267
 
2.1%
Other values (16) 88636
16.4%
Common
ValueCountFrequency (%)
0 3
50.0%
7 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 541059
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 113189
20.9%
U 111068
20.5%
S 106325
19.7%
M 27389
 
5.1%
R 20032
 
3.7%
P 16725
 
3.1%
G 16411
 
3.0%
N 16119
 
3.0%
C 13892
 
2.6%
E 11267
 
2.1%
Other values (18) 88642
16.4%

level0Name
Text

Missing 

Distinct174
Distinct (%)0.1%
Missing157741
Missing (%)46.7%
Memory size2.6 MiB
2025-01-08T17:43:16.189062image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length13
Mean length11.06804988
Min length4

Characters and Unicode

Total characters1996156
Distinct characters61
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st rowUnited States
2nd rowChina
3rd rowKenya
4th rowDjibouti
5th rowUnited States
ValueCountFrequency (%)
united 97300
32.1%
states 97245
32.1%
myanmar 7455
 
2.5%
méxico 4807
 
1.6%
guyana 4333
 
1.4%
philippines 4062
 
1.3%
french 3933
 
1.3%
polynesia 3614
 
1.2%
china 3325
 
1.1%
new 2794
 
0.9%
Other values (202) 73833
24.4%
2025-01-08T17:43:16.425169image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 308073
15.4%
e 235889
11.8%
a 215937
10.8%
i 164095
8.2%
n 156657
7.8%
122348
 
6.1%
s 118233
 
5.9%
d 109469
 
5.5%
S 105440
 
5.3%
U 97741
 
4.9%
Other values (51) 362274
18.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1573656
78.8%
Uppercase Letter 299357
 
15.0%
Space Separator 122348
 
6.1%
Dash Punctuation 528
 
< 0.1%
Other Punctuation 261
 
< 0.1%
Open Punctuation 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 308073
19.6%
e 235889
15.0%
a 215937
13.7%
i 164095
10.4%
n 156657
10.0%
s 118233
 
7.5%
d 109469
 
7.0%
r 36548
 
2.3%
o 33176
 
2.1%
u 30222
 
1.9%
Other values (21) 165357
10.5%
Uppercase Letter
ValueCountFrequency (%)
S 105440
35.2%
U 97741
32.7%
M 16188
 
5.4%
P 15551
 
5.2%
C 12459
 
4.2%
G 9979
 
3.3%
B 5964
 
2.0%
A 5868
 
2.0%
R 4788
 
1.6%
F 4584
 
1.5%
Other values (13) 20795
 
6.9%
Other Punctuation
ValueCountFrequency (%)
, 133
51.0%
. 78
29.9%
' 50
 
19.2%
Space Separator
ValueCountFrequency (%)
122348
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 528
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1873013
93.8%
Common 123143
 
6.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 308073
16.4%
e 235889
12.6%
a 215937
11.5%
i 164095
8.8%
n 156657
8.4%
s 118233
 
6.3%
d 109469
 
5.8%
S 105440
 
5.6%
U 97741
 
5.2%
r 36548
 
2.0%
Other values (44) 324931
17.3%
Common
ValueCountFrequency (%)
122348
99.4%
- 528
 
0.4%
, 133
 
0.1%
. 78
 
0.1%
' 50
 
< 0.1%
( 3
 
< 0.1%
) 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1987453
99.6%
None 8703
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 308073
15.5%
e 235889
11.9%
a 215937
10.9%
i 164095
8.3%
n 156657
7.9%
122348
 
6.2%
s 118233
 
5.9%
d 109469
 
5.5%
S 105440
 
5.3%
U 97741
 
4.9%
Other values (46) 353571
17.8%
None
ValueCountFrequency (%)
é 5680
65.3%
ç 1227
 
14.1%
ã 873
 
10.0%
í 873
 
10.0%
ô 50
 
0.6%

level1Gid
Text

Missing 

Distinct1235
Distinct (%)0.7%
Missing158980
Missing (%)47.0%
Memory size2.6 MiB
2025-01-08T17:43:16.622808image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.591483636
Min length6

Characters and Unicode

Total characters1359741
Distinct characters38
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)< 0.1%

Sample

1st rowUSA.3_1
2nd rowCHN.29_1
3rd rowKEN.20_1
4th rowDJI.3_1
5th rowUSA.2_1
ValueCountFrequency (%)
usa.5_1 10272
 
5.7%
usa.44_1 9642
 
5.4%
usa.3_1 9251
 
5.2%
usa.10_1 8853
 
4.9%
usa.47_1 6219
 
3.5%
mmr.14_1 5452
 
3.0%
usa.21_1 4649
 
2.6%
usa.34_1 4328
 
2.4%
usa.43_1 3079
 
1.7%
usa.32_1 3055
 
1.7%
Other values (1225) 114314
63.8%
2025-01-08T17:43:16.874828image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 235844
17.3%
_ 179114
13.2%
. 179079
13.2%
A 113189
8.3%
U 109841
8.1%
S 106325
 
7.8%
4 56352
 
4.1%
2 42387
 
3.1%
3 40233
 
3.0%
M 27389
 
2.0%
Other values (28) 269988
19.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 537336
39.5%
Decimal Number 464212
34.1%
Connector Punctuation 179114
 
13.2%
Other Punctuation 179079
 
13.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 113189
21.1%
U 109841
20.4%
S 106325
19.8%
M 27389
 
5.1%
R 20032
 
3.7%
P 16722
 
3.1%
G 16411
 
3.1%
N 16110
 
3.0%
C 12662
 
2.4%
E 11267
 
2.1%
Other values (16) 87388
16.3%
Decimal Number
ValueCountFrequency (%)
1 235844
50.8%
4 56352
 
12.1%
2 42387
 
9.1%
3 40233
 
8.7%
5 20947
 
4.5%
0 16021
 
3.5%
9 15545
 
3.3%
7 13298
 
2.9%
6 12329
 
2.7%
8 11256
 
2.4%
Connector Punctuation
ValueCountFrequency (%)
_ 179114
100.0%
Other Punctuation
ValueCountFrequency (%)
. 179079
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 822405
60.5%
Latin 537336
39.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 113189
21.1%
U 109841
20.4%
S 106325
19.8%
M 27389
 
5.1%
R 20032
 
3.7%
P 16722
 
3.1%
G 16411
 
3.1%
N 16110
 
3.0%
C 12662
 
2.4%
E 11267
 
2.1%
Other values (16) 87388
16.3%
Common
ValueCountFrequency (%)
1 235844
28.7%
_ 179114
21.8%
. 179079
21.8%
4 56352
 
6.9%
2 42387
 
5.2%
3 40233
 
4.9%
5 20947
 
2.5%
0 16021
 
1.9%
9 15545
 
1.9%
7 13298
 
1.6%
Other values (2) 23585
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1359741
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 235844
17.3%
_ 179114
13.2%
. 179079
13.2%
A 113189
8.3%
U 109841
8.1%
S 106325
 
7.8%
4 56352
 
4.1%
2 42387
 
3.1%
3 40233
 
3.0%
M 27389
 
2.0%
Other values (28) 269988
19.9%

level1Name
Text

Missing 

Distinct1201
Distinct (%)0.7%
Missing158980
Missing (%)47.0%
Memory size2.6 MiB
2025-01-08T17:43:17.057837image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length28
Mean length9.053652981
Min length3

Characters and Unicode

Total characters1621636
Distinct characters101
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)< 0.1%

Sample

1st rowArizona
2nd rowXizang
3rd rowLaikipia
4th rowDjiboutii
5th rowAlaska
ValueCountFrequency (%)
california 10397
 
4.5%
texas 9642
 
4.2%
arizona 9251
 
4.0%
florida 8853
 
3.9%
virginia 8047
 
3.5%
new 6247
 
2.7%
carolina 6031
 
2.6%
tanintharyi 5452
 
2.4%
maryland 4649
 
2.0%
north 4454
 
1.9%
Other values (1333) 155634
68.1%
2025-01-08T17:43:17.296730image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 229700
14.2%
i 163412
 
10.1%
n 127711
 
7.9%
r 114166
 
7.0%
o 112430
 
6.9%
e 91904
 
5.7%
s 74858
 
4.6%
l 66916
 
4.1%
t 53967
 
3.3%
49543
 
3.1%
Other values (91) 537029
33.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1337352
82.5%
Uppercase Letter 227538
 
14.0%
Space Separator 49543
 
3.1%
Dash Punctuation 6638
 
0.4%
Other Punctuation 559
 
< 0.1%
Modifier Symbol 6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 229700
17.2%
i 163412
12.2%
n 127711
9.5%
r 114166
8.5%
o 112430
8.4%
e 91904
 
6.9%
s 74858
 
5.6%
l 66916
 
5.0%
t 53967
 
4.0%
u 48010
 
3.6%
Other values (54) 254278
19.0%
Uppercase Letter
ValueCountFrequency (%)
C 33751
14.8%
T 24347
10.7%
M 23452
10.3%
A 19365
 
8.5%
S 17430
 
7.7%
N 16131
 
7.1%
V 12256
 
5.4%
F 10777
 
4.7%
P 8121
 
3.6%
O 5900
 
2.6%
Other values (19) 56008
24.6%
Other Punctuation
ValueCountFrequency (%)
' 358
64.0%
/ 136
 
24.3%
, 55
 
9.8%
. 6
 
1.1%
! 4
 
0.7%
Space Separator
ValueCountFrequency (%)
49543
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6638
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1564890
96.5%
Common 56746
 
3.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 229700
14.7%
i 163412
 
10.4%
n 127711
 
8.2%
r 114166
 
7.3%
o 112430
 
7.2%
e 91904
 
5.9%
s 74858
 
4.8%
l 66916
 
4.3%
t 53967
 
3.4%
u 48010
 
3.1%
Other values (83) 481816
30.8%
Common
ValueCountFrequency (%)
49543
87.3%
- 6638
 
11.7%
' 358
 
0.6%
/ 136
 
0.2%
, 55
 
0.1%
. 6
 
< 0.1%
` 6
 
< 0.1%
! 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1608030
99.2%
None 13479
 
0.8%
Latin Ext Additional 127
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 229700
14.3%
i 163412
 
10.2%
n 127711
 
7.9%
r 114166
 
7.1%
o 112430
 
7.0%
e 91904
 
5.7%
s 74858
 
4.7%
l 66916
 
4.2%
t 53967
 
3.4%
49543
 
3.1%
Other values (50) 523423
32.6%
None
ValueCountFrequency (%)
Î 3639
27.0%
é 2945
21.8%
í 2133
15.8%
á 1541
11.4%
ã 1017
 
7.5%
ó 574
 
4.3%
ô 236
 
1.8%
ñ 215
 
1.6%
ü 210
 
1.6%
š 207
 
1.5%
Other values (26) 762
 
5.7%
Latin Ext Additional
ValueCountFrequency (%)
82
64.6%
40
31.5%
3
 
2.4%
1
 
0.8%
1
 
0.8%

level2Gid
Text

Missing 

Distinct4284
Distinct (%)2.5%
Missing167237
Missing (%)49.5%
Memory size2.6 MiB
2025-01-08T17:43:17.497448image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.21143412
Min length8

Characters and Unicode

Total characters1744695
Distinct characters38
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique290 ?
Unique (%)0.2%

Sample

1st rowUSA.3.2_1
2nd rowCHN.29.7_1
3rd rowKEN.20.2_1
4th rowDJI.3.1_2
5th rowUSA.2.9_1
ValueCountFrequency (%)
mmr.14.2_1 3998
 
2.3%
usa.3.2_1 3339
 
2.0%
usa.3.11_1 2680
 
1.6%
usa.9.1_1 2296
 
1.3%
guy.2.8_1 2193
 
1.3%
usa.5.37_1 1794
 
1.1%
usa.26.95_1 1453
 
0.9%
usa.32.26_1 1409
 
0.8%
usa.44.22_1 1372
 
0.8%
mmr.14.3_1 1320
 
0.8%
Other values (4274) 149003
87.2%
2025-01-08T17:43:17.758503image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 341679
19.6%
1 278548
16.0%
_ 170857
9.8%
A 112729
 
6.5%
U 109431
 
6.3%
S 105468
 
6.0%
2 95569
 
5.5%
4 80788
 
4.6%
3 72057
 
4.1%
5 47041
 
2.7%
Other values (28) 330528
18.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 719594
41.2%
Uppercase Letter 512565
29.4%
Other Punctuation 341679
19.6%
Connector Punctuation 170857
 
9.8%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 112729
22.0%
U 109431
21.3%
S 105468
20.6%
M 26536
 
5.2%
R 19482
 
3.8%
N 16096
 
3.1%
G 15657
 
3.1%
C 12491
 
2.4%
P 11988
 
2.3%
E 11168
 
2.2%
Other values (16) 71519
14.0%
Decimal Number
ValueCountFrequency (%)
1 278548
38.7%
2 95569
 
13.3%
4 80788
 
11.2%
3 72057
 
10.0%
5 47041
 
6.5%
6 32059
 
4.5%
0 29267
 
4.1%
7 29047
 
4.0%
9 28157
 
3.9%
8 27061
 
3.8%
Other Punctuation
ValueCountFrequency (%)
. 341679
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 170857
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1232130
70.6%
Latin 512565
29.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 112729
22.0%
U 109431
21.3%
S 105468
20.6%
M 26536
 
5.2%
R 19482
 
3.8%
N 16096
 
3.1%
G 15657
 
3.1%
C 12491
 
2.4%
P 11988
 
2.3%
E 11168
 
2.2%
Other values (16) 71519
14.0%
Common
ValueCountFrequency (%)
. 341679
27.7%
1 278548
22.6%
_ 170857
13.9%
2 95569
 
7.8%
4 80788
 
6.6%
3 72057
 
5.8%
5 47041
 
3.8%
6 32059
 
2.6%
0 29267
 
2.4%
7 29047
 
2.4%
Other values (2) 55218
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1744695
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 341679
19.6%
1 278548
16.0%
_ 170857
9.8%
A 112729
 
6.5%
U 109431
 
6.3%
S 105468
 
6.0%
2 95569
 
5.5%
4 80788
 
4.6%
3 72057
 
4.1%
5 47041
 
2.7%
Other values (28) 330528
18.9%

level2Name
Text

Missing 

Distinct3706
Distinct (%)2.2%
Missing167249
Missing (%)49.5%
Memory size2.6 MiB
2025-01-08T17:43:17.956398image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length29
Mean length8.680839357
Min length2

Characters and Unicode

Total characters1483078
Distinct characters131
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique227 ?
Unique (%)0.1%

Sample

1st rowCochise
2nd rowShigatse
3rd rowLaikipia North
4th rowDjiboutii
5th rowHaines
ValueCountFrequency (%)
of 6496
 
2.8%
san 5277
 
2.3%
kawthoung 3998
 
1.7%
region 3757
 
1.6%
rest 3754
 
1.6%
cochise 3339
 
1.5%
saint 2993
 
1.3%
city 2937
 
1.3%
pima 2680
 
1.2%
columbia 2348
 
1.0%
Other values (3993) 191864
83.6%
2025-01-08T17:43:18.209511image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 169779
 
11.4%
o 113886
 
7.7%
e 111771
 
7.5%
n 109067
 
7.4%
i 102293
 
6.9%
r 76609
 
5.2%
t 66878
 
4.5%
58598
 
4.0%
s 57490
 
3.9%
l 54814
 
3.7%
Other values (121) 561893
37.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1192084
80.4%
Uppercase Letter 220329
 
14.9%
Space Separator 58598
 
4.0%
Dash Punctuation 4331
 
0.3%
Decimal Number 4160
 
0.3%
Other Punctuation 2707
 
0.2%
Open Punctuation 385
 
< 0.1%
Close Punctuation 297
 
< 0.1%
Math Symbol 187
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 169779
14.2%
o 113886
9.6%
e 111771
9.4%
n 109067
 
9.1%
i 102293
 
8.6%
r 76609
 
6.4%
t 66878
 
5.6%
s 57490
 
4.8%
l 54814
 
4.6%
u 50124
 
4.2%
Other values (62) 279373
23.4%
Uppercase Letter
ValueCountFrequency (%)
C 28869
13.1%
S 22774
 
10.3%
M 15767
 
7.2%
B 14864
 
6.7%
L 14643
 
6.6%
P 13514
 
6.1%
A 12476
 
5.7%
D 11771
 
5.3%
R 11687
 
5.3%
K 10475
 
4.8%
Other values (27) 63489
28.8%
Decimal Number
ValueCountFrequency (%)
7 2220
53.4%
9 873
 
21.0%
8 661
 
15.9%
1 210
 
5.0%
3 65
 
1.6%
4 56
 
1.3%
2 36
 
0.9%
5 27
 
0.6%
6 9
 
0.2%
0 3
 
0.1%
Other Punctuation
ValueCountFrequency (%)
' 1550
57.3%
. 714
26.4%
/ 177
 
6.5%
, 165
 
6.1%
& 73
 
2.7%
? 25
 
0.9%
# 3
 
0.1%
Space Separator
ValueCountFrequency (%)
58598
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4331
100.0%
Open Punctuation
ValueCountFrequency (%)
( 385
100.0%
Close Punctuation
ValueCountFrequency (%)
) 297
100.0%
Math Symbol
ValueCountFrequency (%)
+ 187
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1412413
95.2%
Common 70665
 
4.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 169779
 
12.0%
o 113886
 
8.1%
e 111771
 
7.9%
n 109067
 
7.7%
i 102293
 
7.2%
r 76609
 
5.4%
t 66878
 
4.7%
s 57490
 
4.1%
l 54814
 
3.9%
u 50124
 
3.5%
Other values (99) 499702
35.4%
Common
ValueCountFrequency (%)
58598
82.9%
- 4331
 
6.1%
7 2220
 
3.1%
' 1550
 
2.2%
9 873
 
1.2%
. 714
 
1.0%
8 661
 
0.9%
( 385
 
0.5%
) 297
 
0.4%
1 210
 
0.3%
Other values (12) 826
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1469916
99.1%
None 12819
 
0.9%
Latin Ext Additional 343
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 169779
 
11.6%
o 113886
 
7.7%
e 111771
 
7.6%
n 109067
 
7.4%
i 102293
 
7.0%
r 76609
 
5.2%
t 66878
 
4.5%
58598
 
4.0%
s 57490
 
3.9%
l 54814
 
3.7%
Other values (64) 548731
37.3%
None
ValueCountFrequency (%)
é 2769
21.6%
í 2697
21.0%
á 2045
16.0%
ó 1173
9.2%
ê 1152
9.0%
ñ 422
 
3.3%
ú 349
 
2.7%
â 275
 
2.1%
ô 245
 
1.9%
ü 237
 
1.8%
Other values (38) 1455
11.4%
Latin Ext Additional
ValueCountFrequency (%)
171
49.9%
81
23.6%
31
 
9.0%
31
 
9.0%
18
 
5.2%
6
 
1.7%
3
 
0.9%
1
 
0.3%
1
 
0.3%

level3Gid
Text

Missing 

Distinct1717
Distinct (%)4.5%
Missing300258
Missing (%)88.8%
Memory size2.6 MiB
2025-01-08T17:43:18.400467image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length15
Median length14
Mean length11.93075378
Min length11

Characters and Unicode

Total characters451412
Distinct characters34
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique124 ?
Unique (%)0.3%

Sample

1st rowCHN.29.7.10_1
2nd rowKEN.20.2.3_1
3rd rowPAN.12.6.1_1
4th rowPAN.3.3.1_1
5th rowCHN.29.5.1_1
ValueCountFrequency (%)
mmr.14.2.1_1 3995
 
10.6%
mdg.3.5.1_1 907
 
2.4%
pan.3.3.1_1 740
 
2.0%
mmr.14.3.3_1 720
 
1.9%
cri.4.10.3_1 708
 
1.9%
mmr.14.3.1_1 600
 
1.6%
chn.29.5.5_1 570
 
1.5%
ken.20.2.3_1 553
 
1.5%
mdg.6.2.3_1 539
 
1.4%
bol.8.14.1_2 531
 
1.4%
Other values (1707) 27973
73.9%
2025-01-08T17:43:18.656111image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 113508
25.1%
1 78511
17.4%
_ 37836
 
8.4%
2 27108
 
6.0%
3 18840
 
4.2%
M 18153
 
4.0%
4 17781
 
3.9%
R 12466
 
2.8%
5 11565
 
2.6%
C 9801
 
2.2%
Other values (24) 105843
23.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 186566
41.3%
Other Punctuation 113508
25.1%
Uppercase Letter 113502
25.1%
Connector Punctuation 37836
 
8.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 18153
16.0%
R 12466
11.0%
C 9801
8.6%
H 9366
8.3%
N 9192
8.1%
P 8180
 
7.2%
A 7759
 
6.8%
L 7678
 
6.8%
E 4998
 
4.4%
D 3287
 
2.9%
Other values (12) 22622
19.9%
Decimal Number
ValueCountFrequency (%)
1 78511
42.1%
2 27108
 
14.5%
3 18840
 
10.1%
4 17781
 
9.5%
5 11565
 
6.2%
6 7715
 
4.1%
9 7619
 
4.1%
8 6256
 
3.4%
7 5877
 
3.2%
0 5294
 
2.8%
Other Punctuation
ValueCountFrequency (%)
. 113508
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 37836
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 337910
74.9%
Latin 113502
 
25.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 18153
16.0%
R 12466
11.0%
C 9801
8.6%
H 9366
8.3%
N 9192
8.1%
P 8180
 
7.2%
A 7759
 
6.8%
L 7678
 
6.8%
E 4998
 
4.4%
D 3287
 
2.9%
Other values (12) 22622
19.9%
Common
ValueCountFrequency (%)
. 113508
33.6%
1 78511
23.2%
_ 37836
 
11.2%
2 27108
 
8.0%
3 18840
 
5.6%
4 17781
 
5.3%
5 11565
 
3.4%
6 7715
 
2.3%
9 7619
 
2.3%
8 6256
 
1.9%
Other values (2) 11171
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 451412
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 113508
25.1%
1 78511
17.4%
_ 37836
 
8.4%
2 27108
 
6.0%
3 18840
 
4.2%
M 18153
 
4.0%
4 17781
 
3.9%
R 12466
 
2.8%
5 11565
 
2.6%
C 9801
 
2.2%
Other values (24) 105843
23.4%

level3Name
Text

Missing 

Distinct1653
Distinct (%)4.4%
Missing300562
Missing (%)88.9%
Memory size2.6 MiB
2025-01-08T17:43:18.841112image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length29
Mean length8.898300117
Min length3

Characters and Unicode

Total characters333971
Distinct characters111
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique120 ?
Unique (%)0.3%

Sample

1st rowNyalam
2nd rowSegera
3rd rowAncón
4th rowEl Harino
5th rowBomi
ValueCountFrequency (%)
bokpyin 3995
 
8.0%
el 1132
 
2.3%
san 907
 
1.8%
ifanadiana 907
 
1.8%
las 754
 
1.5%
harino 740
 
1.5%
tenasserim 720
 
1.4%
horquetas 708
 
1.4%
poblacion 702
 
1.4%
mergui 600
 
1.2%
Other values (1879) 39014
77.7%
2025-01-08T17:43:19.089750image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 46937
 
14.1%
n 29594
 
8.9%
o 26066
 
7.8%
i 24210
 
7.2%
r 16414
 
4.9%
e 15331
 
4.6%
12647
 
3.8%
u 10324
 
3.1%
g 9540
 
2.9%
s 9502
 
2.8%
Other values (101) 133406
39.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 266145
79.7%
Uppercase Letter 49075
 
14.7%
Space Separator 12647
 
3.8%
Decimal Number 2088
 
0.6%
Other Punctuation 1832
 
0.5%
Open Punctuation 785
 
0.2%
Close Punctuation 782
 
0.2%
Dash Punctuation 617
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 46937
17.6%
n 29594
11.1%
o 26066
 
9.8%
i 24210
 
9.1%
r 16414
 
6.2%
e 15331
 
5.8%
u 10324
 
3.9%
g 9540
 
3.6%
s 9502
 
3.6%
l 9402
 
3.5%
Other values (52) 68825
25.9%
Uppercase Letter
ValueCountFrequency (%)
B 7021
14.3%
M 5183
 
10.6%
S 4536
 
9.2%
T 2935
 
6.0%
P 2922
 
6.0%
C 2900
 
5.9%
A 2557
 
5.2%
H 2425
 
4.9%
L 2402
 
4.9%
I 2316
 
4.7%
Other values (20) 13878
28.3%
Decimal Number
ValueCountFrequency (%)
6 442
21.2%
1 425
20.4%
2 417
20.0%
9 187
9.0%
4 157
 
7.5%
7 136
 
6.5%
5 101
 
4.8%
3 92
 
4.4%
8 83
 
4.0%
0 48
 
2.3%
Other Punctuation
ValueCountFrequency (%)
. 1193
65.1%
, 312
 
17.0%
' 231
 
12.6%
/ 74
 
4.0%
! 22
 
1.2%
Space Separator
ValueCountFrequency (%)
12647
100.0%
Open Punctuation
ValueCountFrequency (%)
( 785
100.0%
Close Punctuation
ValueCountFrequency (%)
) 782
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 617
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 315220
94.4%
Common 18751
 
5.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 46937
 
14.9%
n 29594
 
9.4%
o 26066
 
8.3%
i 24210
 
7.7%
r 16414
 
5.2%
e 15331
 
4.9%
u 10324
 
3.3%
g 9540
 
3.0%
s 9502
 
3.0%
l 9402
 
3.0%
Other values (82) 117900
37.4%
Common
ValueCountFrequency (%)
12647
67.4%
. 1193
 
6.4%
( 785
 
4.2%
) 782
 
4.2%
- 617
 
3.3%
6 442
 
2.4%
1 425
 
2.3%
2 417
 
2.2%
, 312
 
1.7%
' 231
 
1.2%
Other values (9) 900
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 331264
99.2%
None 2516
 
0.8%
Latin Ext Additional 191
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 46937
 
14.2%
n 29594
 
8.9%
o 26066
 
7.9%
i 24210
 
7.3%
r 16414
 
5.0%
e 15331
 
4.6%
12647
 
3.8%
u 10324
 
3.1%
g 9540
 
2.9%
s 9502
 
2.9%
Other values (61) 130699
39.5%
None
ValueCountFrequency (%)
é 537
21.3%
ê 514
20.4%
ñ 263
10.5%
ó 250
9.9%
ơ 194
 
7.7%
í 128
 
5.1%
á 111
 
4.4%
â 87
 
3.5%
ü 86
 
3.4%
à 61
 
2.4%
Other values (22) 285
11.3%
Latin Ext Additional
ValueCountFrequency (%)
83
43.5%
30
 
15.7%
27
 
14.1%
26
 
13.6%
10
 
5.2%
9
 
4.7%
3
 
1.6%
3
 
1.6%

iucnRedListCategory
Text

Missing 

Distinct9
Distinct (%)< 0.1%
Missing63456
Missing (%)18.8%
Memory size2.6 MiB
2025-01-08T17:43:19.145195image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters549276
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNE
2nd rowNE
3rd rowNE
4th rowNE
5th rowNE
ValueCountFrequency (%)
ne 174813
63.7%
lc 87132
31.7%
vu 3277
 
1.2%
nt 3158
 
1.1%
dd 2671
 
1.0%
en 2568
 
0.9%
cr 968
 
0.4%
ex 34
 
< 0.1%
ew 17
 
< 0.1%
2025-01-08T17:43:19.237475image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 180539
32.9%
E 177432
32.3%
C 88100
16.0%
L 87132
15.9%
D 5342
 
1.0%
V 3277
 
0.6%
U 3277
 
0.6%
T 3158
 
0.6%
R 968
 
0.2%
X 34
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 549276
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 180539
32.9%
E 177432
32.3%
C 88100
16.0%
L 87132
15.9%
D 5342
 
1.0%
V 3277
 
0.6%
U 3277
 
0.6%
T 3158
 
0.6%
R 968
 
0.2%
X 34
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 549276
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 180539
32.9%
E 177432
32.3%
C 88100
16.0%
L 87132
15.9%
D 5342
 
1.0%
V 3277
 
0.6%
U 3277
 
0.6%
T 3158
 
0.6%
R 968
 
0.2%
X 34
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 549276
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 180539
32.9%
E 177432
32.3%
C 88100
16.0%
L 87132
15.9%
D 5342
 
1.0%
V 3277
 
0.6%
U 3277
 
0.6%
T 3158
 
0.6%
R 968
 
0.2%
X 34
 
< 0.1%